· We are hiring Entry level/ Junior Software Developer, who is passionate about software programming.

· Polytechnic Diploma in Computer Science, information technology, Software Engineering, or related discipline.

· Exposure to programming skills during academic projects or internship assignment.

· Fresh Graduates or experienced professionals in Software programming.

· Should have strong interest in software programming.

· Should have basic knowledge in ServiceNow Platform.

· Strong analytical /problem solving skills.

· Good communication skills – verbal and written, Good Team Player.

· Good learning attitude and willing to take up challenges

· Well-organised and attentive to details

If anyone If any of these have ever crossed your mind, Consider a switch! FRESH graduates or ORD personnel are welcome!

We’re searching for individuals who want to improve their

communication skillset and improve their skillset! We want you!

At Talent Axis we prioritize our people -they are our greatest asset. We focus on personal growth, soft skills development, and fostering a positive, team-oriented work environment. Our employee consistently expresses their satisfaction and joy when coming into office.

Benefit

✈️travelling opportunities

https://www.handsfreetravel.com/

Your responsibilities

• Identify and analyze existing products and strategies in order to create innovative business approaches and opportunities.
• Monitor industry trends, competitive landscape, and product design and development in the marketplace to help create innovative product ideas.
• Work with cross-functional teams such as engineering and marketing to transform creative ideas into functional, saleable products and services.
• Conceive new and improved features by working closely with customer-focused teams to understand customer needs and transform them into product initiatives.
• Develop product roadmaps and manage the whole product lifecycle: from inception and prioritizing new features to final delivery.
• Regularly conduct feasibility studies and market research on potential product releases.
• Track metrics post-launch, to ensure products are delivering against key performance indicators.
• Make strategic and data driven decisions to prioritize certain product features over others and adjust as necessary.
• Deep strategic analysis to answer core questions such as: How can we help advertisers see better performance? Why do SMB advertisers churn? Who should our target audience be?
• Opportunity sizing and analysis. Write clear, actionable analyses that help teams identify areas of improvement and investment.
• Improve decision velocity and quality using data scientist tool kit: experimentation, causal inference techniques, etc. Design measurement strategy, advise on experimentation best practices, identifying flaws in experiment practices and results; building tools for experiment analysis etc.
• Creating and tracking success metrics. Identify the right measures of success for engineering teams and help them track those metrics. Break down high-level metrics into actionable segments. This work may span from collecting entirely new datasets to building dashboards to track components of a metric.

What you'll need to succeed

• Proven experience as a Product Manager (at least 5 years related working experience), with a track record of managing all aspects of a successful product throughout its lifecycle.
• Understanding in software development knowledge, can communicate well with customers and development
• Ability to analyze data and iteratively optimize products based on data
• Ability to create and deliver presentations tailored to the audience needs.
• Strong problem-solving skills, coupled with effective communication and adept decision-making capabilities.
• Good project management skills with the ability to balance multiple concurrent projects.
• Experience with driving the product vision, go-to-market strategy and design discussions.
• Bachelor's degree in a relevant field.
• 5+ years of combined post-graduate academic and industry experience applying scientific methods to solve real-world problems on web-scale data.
• Strong background in statistics, machine learning, and/or experimentation
• Domain knowledge in advertising and product development.

As a highly collaborative organization, our data engineers work cross-functionally with software engineering, data science, and product management to optimize growth, strategy, and experience for our 3 billion plus users, as well as our internal employee community. In this role, you will see a direct correlation between your work, company growth, and user satisfaction. Beyond this, you will work with some of the brightest minds in the industry, and you'll have a unique opportunity to solve some of the most interesting data challenges with efficiency and integrity, at a scale few companies can match.

RESPONSIBILITIES

• Manage and execute data warehouse plans for a product or a group of products to solve well-scoped problems
• Identify the data needed for a business problem and implement logging required to ensure availability of data, while working with data infrastructure to triage issues and resolve
• Collaborate with engineers, product managers and data scientists to understand data needs, representing key data insights in a meaningful way
• Build data expertise and leverage data controls to ensure privacy, security, compliance, data quality, and operations for allocated areas of ownership
• Design, build and launch new data models and visualizations in production, leveraging common development toolkits
• Independently design, build and launch new data extraction, transformation and loading processes in production, mentoring others around efficient queries
• Support existing processes running in production and implement optimized solutions with limited guidance
• Define and manage SLA for data sets in allocated areas of ownership

MINIMUM QUALIFICATIONS

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
• 2+ years of work experience in data engineering
• Experience with SQL, ETL, data modeling, and at least one programming language (e.g., Python, C++, C#, Scala, etc.)

PREFERRED QUALIFICATIONS

• Experience with one or more of the following: data processing automation, data quality, data warehousing, data governance, business intelligence, data visualization, data privacy
• Experience working with terabyte to petabyte scale data

Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.

Description

• Design, develop, and maintain scalable data pipelines using Spark and Scala to process large datasets.

• Implement and manage Elasticsearch clusters for efficient data retrieval and analysis.

• Collaborate with data scientists and analysts to understand data requirements and provide support for analytical solutions.

• Utilize Quantexa for entity resolution and network analytics to enhance data quality and insights.

• Monitor and optimize data workflows for performance, reliability, and scalability.

• Document data processes and ensure best practices in data engineering are followed.

• Participate in code reviews and contribute to the continuous improvement of our data engineering practices.

Requirements

• Proven experience as a Data Engineer, with a strong focus on Spark and Scala.

• Proficiency in Elasticsearch for search and analytics applications.

• Familiarity with Quantexa or similar tools for data enrichment and entity resolution.

• Experience with cloud platforms (AWS, Azure, GCP) is a plus.

• Strong SQL skills and experience with relational databases.

Description

• Design, develop, and maintain scalable data pipelines using Spark and Scala to process large datasets.
• Implement and manage Elasticsearch clusters for efficient data retrieval and analysis.
• Collaborate with data scientists and analysts to understand data requirements and provide support for analytical solutions.
• Utilize Quantexa for entity resolution and network analytics to enhance data quality and insights.
• Monitor and optimize data workflows for performance, reliability, and scalability.
• Document data processes and ensure best practices in data engineering are followed.
• Participate in code reviews and contribute to the continuous improvement of our data engineering practices.

Requirements

• Proven experience as a Data Engineer, with a strong focus on Spark and Scala.
• Proficiency in Elasticsearch for search and analytics applications.
• Familiarity with Quantexa or similar tools for data enrichment and entity resolution.
• Experience with cloud platforms (AWS, Azure, GCP) is a plus.
• Strong SQL skills and experience with relational databases.

Job Summary:

An exciting opportunity for Data Engineer to be a part of a project for strategic initiatives in architecting, designing and building next-generation cloud-based data platforms.

Mandatory Skill-set:

• Degree in Data Engineering, Computer Science, Information Technology;
• At least 5 years of experience in data engineering and modelling;
• Strong hands-on exposure in data science, data analytics and / or data engineering;
• Deep understanding of system design, data structure and algorithms, data modelling, data access, and data storage;
• Have experience with Big Data platforms such as Hadoop, Spark, and NoSQL databases;
• Advanced SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases;
• Good understanding in using cloud technologies such as AWS, Azure, and Google Cloud;
• Experience with orchestration frameworks such as Azure Data Factory, Airflow;
• Proficiency in programming languages such as Python, R, Java, or Scala;
• Familiarity with building and using CI/CD pipelines;
• Familiarity with DevOps tools such as Git, Terraform, Git;
• Strong hands-on exposure with ETL Extract, Transform, Load tools;
• Possess strong written and verbal communication abilities, effectively conveying information to various stakeholders.

Desired Skill-set:

• Experience in designing, building, and maintaining batch and real-time data pipelines;
• Experience with Databricks or Snowflake.

Responsibilities:

• Work closely with the various team in architecting, designing and building ingestion pipelines to collect, clean, merge, and harmonize data from different source systems;
• Involved in architecting and scaling data analytics infrastructure on cloud environment; development of systems, architectures, and platforms that can scale large volume and variety;
• Architect and build ingestion pipelines to collect, clean, merge, and harmonize data from different source systems;
• Improve and optimize the workloads, processes to ensure that performance levels can support continuous accurate, reliable, and timely delivery of data products; ensure maximum database uptime;
• Monitoring of databases and ETL systems for database capacity planning and maintenance, monitoring, and performance tuning; diagnose issues and deploy measures to prevent recurrence;
• Construct, test, and update useful and reusable data models based on business data needs;
• Engagement and collaboration with product managers, software engineers, data analysts and data scientists to build scalable and data-driven platforms and tools;
• Collaborate with data stewards to establish and enforce data governance policies, best practices and procedures;
• Assist to maintain master data catalogue to document data assets, metadata and lineage;
• Implement and enforce data security best practices, including access control, encryption, and data masking, to safeguard sensitive data;
• Involved in managing production services that provide analytics capabilities to our various data users across the division.

About Bytedance

Founded in 2012, ByteDance's mission is to inspire creativity and enrich life. With a suite of more than a dozen products, including TikTok, as well as platforms specific to the China market, including Toutiao, Douyin, and Xigua, ByteDance has made it easier and more fun for people to connect with, consume, and create content.

Why Join Us

Creation is the core of ByteDance's purpose. Our products are built to help imaginations thrive. This is doubly true of the teams that make our innovations possible. Together, we inspire creativity and enrich life - a mission we aim towards achieving every day. To us, every challenge, no matter how ambiguous, is an opportunity; to learn, to innovate, and to grow as one team. Status quo? Never. Courage? Always. At ByteDance, we create together and grow together. That's how we drive impact - for ourselves, our company, and the users we serve. Join us.

About the Team

Nuverse is a gaming business unit in ByteDance. The Game Technology team is playing a significant role in the whole life cycle of the game. We are responsible for the development, testing, operation, SRE, and quality assurance of the user and operating system, and give strong support for game developing and publishing. Providing comprehensive and systematical solutions, support the good operation and commercialization of the game. Responsible for the design and implementation of the deployment architecture of the game's overseas game business, and ensuring the good operation of online services.

Job Description:

1. Participate in the construction and operation and maintenance of offline and real-time data warehouses for game business;

2. Participate in the optimization of the data ETL process and solve ETL-related technical problems;

3. Participate in data governance work under complex data link dependencies and multi-data content ecology;

4. Relying on ByteDance's big data solutions, quickly implement data solutions in the business.

Qualifications

Minimum Qualifications：

1. Bachelor's degree or above in computer-related majors, with more than 4 years of big data-related work experience;

2. Master most of the big data-related technologies such as Hive, Yarn, Spark, Flink, Kafka, HBase, understand their principles and be able to complete performance tuning;

3. Proficient in using HQL, and master at least one of Python, Java, Scala, and GO;

4. Familiar with the Linux operating system and proficient in Shell programming;

5. Be proactive at work and be able to independently analyze and solve problems;

6. Be responsible, have good communication skills and teamwork ability;

Preferred Qualifications:

1. Experience in the gaming industry or managing platform-type internet products will be an advantage.

ByteDance is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At ByteDance, our mission is to inspire creativity and enrich life. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too.

Balyasny Asset Management (BAM) is a global, multi-strategy investment Firm with over $21 billion in assets under management. We are a diversified business, with global breadth and depth. Our Firm has a clear mission: To consistently deliver uncorrelated returns in all market environments. Today, BAM employs more than 160 portfolio managers and 1,200 investment professionals across 19 offices in the U.S., Europe, the Middle East, and Asia. We are active across six investing strategies: Equities Long/Short, Equities Arbitrage, Macro, Commodities, Systematic, and Growth Equity. We also have a dedicated private investment team, BAM Elevate, and a standalone equities unit, Corbets Capital.

As a Data Scientist on our Applied AI Team at BAM, you will:

• Work collaboratively with senior AI engineers and quantitative researchers to research and build AI systems
• Devise and develop AI solutions that leverage cloud-based data and distributed computing technologies
• Assist with managing the AI software development cycle including setting up and maintaining CI/CD pipelines
• Provide support for the system and be proactive in resolving issues in a timely manner
• Work as part of a globally distributed yet close-knit team. Be an active participant in feature brainstorming, technical design sessions, code reviews, and general interaction
• Create software that is well-commented, well-understood, well-tested, and well-documented: Quality above all!

To be considered a good cultural fit, you must be:

• An ambitious self-starter
• Driven, self-motivated, and creative
• Hungry to learn
• Driven towards success
• A very strong and efficient communicator
• Able to multi-task and excel in a fast-paced trading environment
• A problem solver; able to develop quick and sound solutions to complex problems
• Humble, self-aware, and willing to risk pushing back to make the team and others better

To be considered a good technical fit, you must have:

• Postgraduate degree in a quantitative discipline such as Computer Science, Data Science, Statistics or Mathematics
• 3+ years of professional experience developing high quality Data solutions and products as an individual contributor
• A passion for data and AI, and experience harnessing that passion to educate others
• Strong knowledge of AI engineering best practices, object-oriented concepts, and the ins and outs of data-focused development
• Expert in Python (including its data wrangling and machine learning libraries)
• Solid understanding and demonstrable experience applying natural language processing, large language models and machine learning to solve real business problems
• Familiarity with a wide variety of LLM architectures, including the GPT, Llama, Mixtral and Claude models
• Experience customizing LLMs for specific applications using fine-tuning techniques, (e.g. PEFT), RAG and prompt engineering is big plus
• Experience evaluating and benchmarking LLMs using frameworks such as Arthur Bench is big plus
• Experience with the entire AI software development cycle from design to deployment e.g. using frameworks such as LangChain is a big plus
• Experience with basic DevOps techniques, including CI/CD and infrastructure-as-code
• Experience working in at least one cloud environment. Familiarity with AWS is a big plus

Bonus points for:

• Research publications in leading journals and presentations at internationally renowned conferences
• Teaching experience and the development of training material for AI use-cases
• Experience developing models for named-entity recognition
• Financial industry experience, though this is not required for the role

Don’t have all the skills listed above? Have extra skills you think are important that we haven’t thought of? Please, let us know by applying and telling us a bit more about yourself and why you think you’re qualified!

KPMG in Singapore is part of a global organization of independent professional services firms providing Audit, Tax and Advisory services. We operate in 143 countries and territories with more than 273,000 partners and employees working in member firms around the world. Each KPMG firm is a legally distinct and separate entity and describes itself as such. KPMG International Limited is a private English company limited by guarantee. KPMG International Limited and its related entities do not provide services to clients.

Job Description

At KPMG, your long-term future is every bit as important to us as it is to you. That’s why our aim is to give you experiences that will stay with you for a lifetime. Whether it’s great training and development, working across functional sectors, mobility opportunities or corporate responsibility volunteering activities – you’ll gain a wealth of experiences on which to build a rewarding career. We’re proud of our culture – it’s one that recognises hard work, encourages new ways of thinking and embraces diversity and inclusion. We have an innovative spirit which inspires what we do and how we do it – striving to be better lies at the heart of who we are.

KPMG Cybersecurity professionals assist clients to address their concerns around Confidentiality, Integrity, Availability and Privacy of their technology, business systems, and information assets. Using a holistic view of how Technology and Business integrate, the Cyber team performs technology-risk focused assessments, technology compliance, IT/operational process reviews, and design of information risk & cyber security solutions.

Cyber team members regularly interact with C-Suite clients, such as Chief Executive Officer (CEO), Chief Information Security Officer (CISO), Chief Information Officer (CIO), Chief Operating Officer (COO), Chief Risk Officer (CRO) and their direct reports. Hence, a client centric mind-set, understanding of IT within a Business context, and well-developed communication skills are desirable.

The role involves:

• Engage with client stakeholders on Data protection Projects.
• Providing in-depth expertise of Data protection.
• Conducting discovery workshops for customers to understand their data protection measures and recommend improvements to their security posture.
• Work with customers to plot their cloud journey and advising them on their overall data protection requirements based on their data landscape.
• Working with KPMG Project and Customer resources to continue design and deployment activities and further enhance Data protection solutions for our customers.
• Working with customers and leading data protection vendors to design and build creative solutions.
• Working with team members, you will design and/or build solutions within large transformations, and you will perform reviews, assessments and build strategies for organizations looking to invest in Data protection.
• Assisting the engagement manager with the planning and delivery phases of engagements.

⠀

The ideal candidate should possess:

• Bachelor’s degree in Computer Science, Computer/Electrical Engineering, Information Technology or equivalent.
• A highly motivated individual in information security and excellent communicator with strong analytical and good problem-solving skills.
• Minimum 5 years of relevant experience working on Data protection technologies: Forcepoint, Proofpoint, Varonis, Zscaler, MSFT Purview
• Good understanding of Security strategy, assessment, and design and implementation and governance frameworks over processes, controls, organisation and infrastructure.
• Proven technical knowledge in Data Governance, Data classification, Data loss prevention, Insider threat, Data encryption, CASB etc.
• Good understanding of cloud platforms like Microsoft Azure, Google and AWS.
• Proficient in PowerShell and Python
• Strong understanding and hands-on experience with Windows OS, including Active Directory and DNS.
• Understanding of creating and managing virtual machines, EC2 instances, VNETs, VPCs, and access control management.
• Experience in implementing and managing firewalls, VPNs, and intrusion detection/prevention systems.
• Ability to respond to security incidents, conduct root cause analysis, and implement corrective actions.
• Familiarity with industry standards and regulations such as GDPR, HIPAA, or ISO 27001, Personally Identifiable Information (PII) ensuring compliance in security practices.
• Excellent business analysis experience in requirements gathering, modelling use cases and experience in business development in supporting new business offerings.
• Any relevant industry related certification will be preferred (e.g. CISSP, AWS , AZURE , Data protection product certifications etc.)

Only shortlisted candidates will be contacted by KPMG Talent Acquisition team, personal data collected will be used for recruitment purposes only.

At KPMG in Singapore we are committed to creating a diverse and inclusive workplace. We believe that diversity of thought, background and experience strengthens relationships and delivers meaningful benefits to our people, our clients and communities. As an equal opportunity employer, all qualified applicants will receive consideration for employment regardless of age, race, gender identity or expression, colour, marital status, religion, sexual orientation, disability, or other non-merit factors. We celebrate the different talents that our people bring and support every staff member in their journey to achieve personal and professional growth. One of the ways we do this is through Take Charge: Flexi-work, our flexible working framework which enables agile and innovative teams to help deliver our business goals.

We are seeking a talented and a motivated Senior Data Engineer to join our dynamic team. As a Senior Data Engineer, you will be responsible for designing, implementing, and maintaining scalable data pipelines and infrastructure to support our data-driven initiatives. You will collaborate closely with cross-functional teams to understand data requirements, optimize data models, and ensure the reliability and performance of our data systems.

Key Responsibilities:

 Design, develop, and maintain robust data pipelines to ingest, process, and transform large volumes of structured and unstructured data from various sources (e.g., Database, API, SFTP).

 Build and optimize data models and schemas to support efficient data storage, retrieval, and analysis.

 Implement data integration solutions to consolidate data from disparate systems and sources.

 Work closely with Data Scientists and Analysts to understand their requirements and provide them with clean, reliable, and well-structured data.

 Collaborate with DevOps and Infrastructure teams to deploy and manage data infrastructure in cloud environments (e.g., AWS, Azure).

 Familiar with the concept of data security to ensure the data pipelines are secured and PII (Personally Identifiable Information) data are encrypted.

 Monitor and optimize the performance, scalability, and reliability of data systems to ensure high availability and low latency.

 Design and develop MLOps production pipelines; provide technical support to data scientists/ML engineers by getting their ML/DL models deployed at scale and meeting SLAs on both cloud and on-premises GPU and CPU instances.

 Develop and maintain documentation, standards, and best practices for data engineering processes and technologies.

 Stay current with emerging technologies and trends in data engineering and contribute to the continuous improvement of our data architecture and practices.

 Explore, evaluate, and champion the introduction of next-generation technologies in the data-ingestion workflow. Participate in project planning and provide technical guidance on cloud architecture for data projects.

Requirements:

 BS in Computer Science or other related discipline is required. Advanced degrees in Computer Science (PhD, MS) are highly desirable.

 Proven experience (3 years) working as a Data Engineer or in a similar role.

 Strong proficiency in programming languages such as Python. Conversant with data structures and algorithm design.

 Hands-on experience with distributed computing frameworks and big data technologies such as Spark, Kafka, etc.

 Proficiency in SQL and experience with relational databases (e.g., Azure SQL DB, AWS Redshift).

 Experience with data modelling, ETL/ELT processes, and data warehousing concepts.

 Familiarity with cloud platforms and services (e.g., AWS S3, AWS Step Functions, AWS Airflow, Azure Data Logic Apps, Azure Blob Storage).

 Experience with setting up SSO using AD and implementing RBAC (Role Based Access Control) for data security.

 Excellent problem-solving skills and attention to detail.

 Effective communication and collaboration skills, with the ability to work effectively in a cross-functional team environment.

 Experience with version control systems (e.g., Git) and CI/CD pipelines is a plus.

Artefact is the next generation end-to-end data service company, with a focus on consulting and marketing, that helps organizations transform data into value and business impact.

Our broad range of data-driven solutions in data consulting and digital marketing are designed to meet our clients’ specific needs, always conceived with a business-centric approach and delivered with tangible results.

We have 1000+ employees across 18 offices who are focused on accelerating digital transformation. Thanks to a unique mix of company assets: State of the art data technologies, lean AI agile methodologies for fast delivery, and cohesive teams of the finest business consultants, data analysts, data scientists, data engineers, and digital experts, all dedicated to bringing extra value to every client.

Responsibilities

With the support of a Junior Data Consultant, you will have the opportunity to carry out various projects independently and in collaboration with Artefact’s teams of experts: Strategy, Activation, Analytics, Data, Creation.

At the agency or at the client’s premises, the consultant is a true project manager. The diversity of your missions will allow you to be as close as possible to customer issues, to acquire a real knowledge of data and to quickly develop your skills.

Your missions will include:

• define the needs of its customers by conducting interviews with customer teams and multiple technology partners,
• to help build, formulate and present strategic data recommendations for the client,
• to organize and conduct workshops and training to ensure the success of its projects,
• to develop and present data recommendations to clients,
• to imagine and present new support proposals to convince our future customers,
• to participate in training courses to acquire the technical knowledge necessary for its mission as an advisor and to keep abreast of the latest technological innovations on the market,
• and finally to participate in the writing of content on transversal subjects (e.g. publication of research works, writing articles or business cases).

Requirements

• Graduated from a business school (desired), the most important qualities in our eyes are intellectual curiosity, autonomy and dynamism.
• A first knowledge of digital marketing (within a start-up, agency, etc.) or consulting (Strategy, Management, IS), will obviously be valued.

• Min 8 years of experience.
• At least 8 years of data-related working experience, with at least 5 years of hands-on experience in data management and data analytics in the finance, investment, banking, and asset management industries.
• Good understanding of the principles, key controls and processes relating to data management.
• Good at working with details and is meticulous in operations and tasks.
• Good understanding of data modelling.
• Good understanding on OLTP, Data Lake, Lakehouse technologies that may include knowledge of Snowflake, S3, AWS Glue, DeltaLake, DataBricks.
• Good understanding of CI/CD pipelines, DevOps, DataOps, and their applicability in financial services.
• Experience in working with databases using database technologies (e.g. MS SQL, Snowflake, Redshift and PostgreSQL) and data integration products (e.g. Informatica, Data Factory, Bash).
• Extensive data-related experience in programming languages eg Python, SQL, Scala, Javascript, and similar.
• Experience in working with business intelligence and data visualization tools e.g. Tableau, PowerBI.
• Experience with SDLC methodology and/or agile methodologies like Scrum and Kanban and its related applications eg Confluence and JIRA.
• Good team player, with strong analytical skills and enjoys complex problem solving.
• Experience in data engineering platforms and virtualization eg Denodo, Jupyter, O365.
• Excellent written and spoken English and strong presentation skillsets.
• Strong inter-personal and people leadership skills to interact with diverse stakeholders.

Responsibilities:

• Working closely with data analysts and business end-users to implement and support data platforms using best-of-breed technology and methodology.
• Implement and design robust and scalable solutions to meet business needs and take operational considerations into account. Demonstrate technical expertise in the assigned areas.
• Manage operations and maintain SLAs. Implement automation in data management. Collaborate with data engineering, architecture, and governance.
• Perform data and metadata quality, modeling, lineage, cleansing, onboarding, registration, discoverability, access controls, migration, optimization, and cataloging. Execute, maintain and manage the whole data lifecycle.
• Conduct requirement workshops with stakeholders, analyze and translate business and other requirements holistically into data strategies, plans, and actions.
• Cover all aspects of data distribution and data service.
• Design and implement scalable data pipelines and data service modules with robustness in mind to support the growing demands from business users.
• Analyze and resolve day-to-day operational incidents and advisory to business users.
• Listen to upstream changes, perform impact analysis and mitigate-modify-implement.
• Do impact analysis, inform and distribute to downstream users and applications.
• Analyze systems operations data (SLAs, customer satisfaction, delivery quality, team efficiency etc.) to identify actionable trends for continual improvements.
• Data, application, and system checking and testing (eg UAT), CICD and go-live.

About Us
We are living in dynamic times. Technology is reshaping how we live, and we want to use it to redefine how financial services are offered. This is why we are coming together to unlock big dreams, and financial inclusion for people in our region is just one of them. We want to build a digital bank with the right foundation - using data, technology and trust to solve problems and serve customers.

We're seeking a driven and skilled Credit Risk Data Scientist to join our dynamic team. If you're passionate about predictive modelling, risk management, and leveraging cutting-edge technologies, this role offers an exciting opportunity to contribute in two key areas:

Credit Risk Models:

• Develop, maintain, and monitor predictive models for credit scoring, fraud detection, and suspicious activity prediction.
• Write high-quality, production-ready code for models to be deployed in the production environment.
• Deploy models in the MLOps production environment, maintaining and troubleshooting any issues.
• Support regular model performance reviews, audits, and recalibrations.
• Leverage alternative data sources to enhance underwriting and credit risk models.
• Ensure alignment with model governance, business, and regulatory expectations.

Data Analytics to Help Business:

• Collect, process, and analyze data to support statistical analysis and risk decision-making.
• Design, implement, and maintain performance reports and actionable insights dashboards.
• Provide data-driven insights and develop dashboards to support loan approval processes and business decision-making.
• Conduct in-depth analyses to identify trends, patterns, and anomalies in lending data that can influence credit risk strategies.
• Present model concepts and metrics to senior stakeholders and validators/auditors.

Experience and Qualifications

• Degree (PhD, Master's, Bachelor's) in Statistics, Mathematics, Economics, Finance, Risk Management, or related field.
• Proven experience building risk models such as Application Score, Behavior Score, PD, EAD, LGD (Basel or IFRS 9), especially for retail customers in diverse countries including Singapore.
• Comprehensive understanding of risk management throughout the customer journey within fintech or risk-focused environments.
• Domain expertise in retail credit products, banking, and regulatory frameworks (Basel, IFRS).
• Proficiency in Python, R, SQL, Snowflake and Data Visualization tools like Tableau.
• Technical proficiency in data retrieval, data modeling, data mining, and predictive modeling.
• Strong familiarity with advanced machine learning techniques, statistical classification/regression for credit risk.
• Exceptional problem-solving skills, detail-oriented mindset, and ability to thrive in a dynamic work setting.
• Bonus: Familiarity with implementing models using Terraform scripts, Docker/Kubernetes, CI/CD technologies, AWS, or MLOps.

Responsibilities:

· Engage with clients to understand their business objectives, challenges, and requirements related to AI and Data solutions.

· Conduct discovery sessions to gather relevant information and identify opportunities where AI, LLM and Data Platforms can add value.

· Utilize knowledge of Data & AI capabilities to create compelling demonstrations tailored to client needs. Showcase how AI/LLMs can address specific use cases and deliver tangible business outcomes.

· Lead the execution of Proof of Concepts to validate the feasibility and effectiveness of solutions in addressing client requirements. Define success criteria, design POC workflows, and oversee the implementation process.

· Provide expert guidance and consultation to clients on technical aspects of Data Platforms, AI platforms, LLM technologies, fine-tuning methodologies, and model quantization techniques. Address client queries, offer insights, and recommend best practices of AI and Data Platforms

· Work closely with sales teams to support the development of winning proposals and presentations.

· Stay updated on industry trends, emerging technologies, and advancements in AI and Data domains. Share knowledge internally through training sessions, workshops, and documentation to empower sales teams and enhance organizational expertise.

· Cultivate strong relationships with clients, fostering trust and confidence in the capabilities of Data and AI platforms. Act as a trusted advisor, understanding their evolving needs and aligning solutions accordingly.

Maltem Singapore is currently seeking Data Engineers for our Wealth Management Client.

Summary:

The successful candidate will be involved in the creation of solutions for Data Services automation.

Skillset Requirements:

• Possess a degree in Computer Science/Information Technology or related fields.
• Proficient in Python
• SQL
• PL/SQL
• CICD.
• Familiarity with Data Warehouses such as Snowflake AND Oracle.
• Strong analytical and problem-solving skills.
• Good team player and communication skill.

Good-To-Have:

• Denodo

Role Summary: The Data & AI Project Manager is responsible for leading data analytics and AI initiatives across both internal and external teams, ensuring that all projects align with the agency’s strategic goals and deliver valuable insights. This role manages the lifecycle of data and AI projects, from planning and development through to implementation and optimization, working with both vendors and internal data specialists.

Key Responsibilities:

• Vendor and Internal Team Coordination:
  • Manage relationships with external data and AI vendors while also leading internal data teams (local or overseas) to align on project priorities, timelines, and deliverables.
  • Facilitate collaboration between internal and vendor teams, ensuring clear roles and responsibilities and efficient information flow.
  • Regularly review and manage the distribution of work between internal teams and vendors to optimize resources.
• Data Strategy and AI Project Management:
  • Develop and drive a comprehensive data and AI strategy, identifying projects that provide the highest business value.
  • Define project KPIs, set clear success criteria, and establish metrics to measure the effectiveness of both in-house and outsourced data/AI initiatives.
  • Ensure alignment of all data initiatives with business needs, prioritizing projects based on their impact on business performance.
• Requirements Documentation and Solution Design:
  • Work closely with stakeholders to capture data requirements and document them into actionable project plans for internal teams and vendors.
  • Provide guidance on technical requirements, data integrity, and quality standards for AI models and analytics projects.
• Quality Assurance and Validation:
  • Oversee quality assurance for data and AI outputs, ensuring deliverables are accurate, reliable, and aligned with strategic objectives.
  • Lead UAT and feedback loops with stakeholders, coordinating with both vendors and internal teams for adjustments and refinements as needed.
  • Implement validation processes to confirm the accuracy of insights, allowing business teams to confidently apply findings.
• Reporting and Continuous Improvement:
  • Track and report on project outcomes, including impact assessments, user adoption metrics, and ROI for each AI and data project.
  • Encourage knowledge sharing between internal and vendor teams, implementing a continuous improvement process for data practices and AI model accuracy.

Overall (10) years of IT / Data Engineering experience.

At least (3) years of relevant experience in:

• Business Requirement Analysis
• Business Process and System Understanding
• Effective Communication with both business and technical users
• Conversant in Microsoft Office products

At least (2) years of hands-on experience as Azure Data Engineer using:

• Azure Data Factory
• Azure Synapse Analytics / Datawarehouse

At least (3) years of hands-on experience in:

• Performing data Ingestion using Data factory & T-SQL stored procedure and data harmonizing
• Implementing Data Quality validation
• Good to have following skills
• Knowledge of Azure Databricks
• Data modelling in Azure Analysis Services using star and snowflake schema
• Python Coding Experience

Required qualifications Bachelors of Engineering

✨Lead with Purpose, Ignite New Opportunities, and Shape your Future!✨

We are one of the leading Sales & Marketing company assisting our established clients in providing them a one-stop solution to increase their sales revenues and market shares through face-to-face marketing.

We are looking to develop the next talent from scratch in our industry to a business partner in the future. If you have the desire, our systems have set many talents just like you!

What you will be doing:
- Ensure customer satisfaction

✨Lead with Purpose, Ignite New Opportunities, and Shape your Future!✨

We are one of the leading Sales & Marketing company assisting our established clients in providing them a one-stop solution to increase their sales revenues and market shares through face-to-face marketing.

We are looking to develop the next talent from scratch in our industry to a business partner in the future. If you have the desire, our systems have set many talents just like you!

What you will be doing:
- Ensure customer satisfaction

Job Description

- Preparation of documents (e.g. order processing, verifying payment, delivery orders).
- Liaise with various stakeholders to ensure smooth delivery.
- Data entry and maintenance of database.
- Maintain and update sales records and ensure files are backed up.
- Assist in new IMS (Inventory Management System) Implementation.
- Provide administrative support to sales team.
- Assist in monthly sales closing.

Job Requirement

- Good interpersonal skills
- Proficient in MS Office Suite
- Experience in data entry is preferred

Interested applicants pls send in a copy of your resume with your current, expected salaries and availability in Microsoft Word format to Low See Wei (R1551122) for immediate processing.

Kindly indicate in your email subject title as "Job Application for 19359 Sales Admin Assistant (Temporary 6 month, Sale Coordinator, Data Entry) SW228"

Only shortlisted candidates will be notified, other applications will be updated to our database for future job opportunities

Thank you.

By submitting any resumes or applications to Pasona Singapore Pte Ltd, you are considered to have read and agreed on the terms of our Privacy Policy, and consented to us collecting, using, retaining, disclosing your personal information to the prospective employers for their consideration.

Please find Privacy Policy Agreement from the below link.

http://www.pasona.com.sg/privacy.html