Total 1 product specialist job vacancies in Singapore

Job Purpose

The Finance Data Specialist plays a critical role in the execution of our APLL Finance transformation mandate by actively supporting data-driven business intelligence initiatives. This role will act as a bridge between Finance, business units and IT. It requires close collaboration with cross-functional teams in understanding business requirements and designing and developing the data architecture for BI solutions and visualization. Key deliverables include proactively providing timely, reliable and easy-to-use financial information and valuable and actionable insights to help drive high-impact business changes and strengthen financial performance analytics.

Roles & Responsibilities

Data Governance, Strategy and Collections

• Support the development and execution of Finance data, governance and analytics strategy and roadmap.
• Collaborate with finance and business stakeholders to understand business logic and their analytics needs, identify data metrics and document the requirements.
• Translate business needs into specifications and data requirements. integrate business and financial data to establish a solid foundation for financial analysis or reporting solutions.
• Work closely with business partners and IT to design, define and develop end-to-end data pipelines for BI solutions: build instrumentation and define dimensional models, tables or schemas that support business processes.
• Contribute to the development and maintenance of databases and data pipelines. This ensures data quality and accessibility for analysis.
• Gather data from various sources (databases, APIs, web scraping, etc.), clean it, and transform it into a usable format. This often involves dealing with datasets that have challenges including missing values, lump sum amounts, inconsistencies, and different data types.
• Design, write and support extract, transform, and load (ETL) processes of finance and business operations data from various sources, deliver insightful data findings for business success

Data Analytics and Business Intelligence

• Conduct “deep dive” reviews of financial data to uncover trends and patterns. Deploy different types of advance data analytics to identify anomalies, outliers and leakages in transactions to mitigate risks and optimize profit.
• Align with stakeholders on key metrics, design and propose experimentation strategies to continually raise the bar on our analytical capabilities
• Ensure data accuracy by mining, cleaning, and analyzing large datasets for effective use-case development of BI and dashboard visualization solutions.
• Interpret results using a variety of techniques, ranging from simple data aggregation via statistical analysis to complex data mining.
• Develop, optimize financial reporting and enhance data automation to enable reliable self-service reports and streamline financial closing process.
• Use BI tools to create compelling data visualization and dashboards to generate timely, meaningful and actionable insights in driving critical business decision making.
• Predictive Modelling: Building models to forecast future outcomes based on historical data. This can involve machine learning techniques like regression, classification, and clustering.
• Support projects or gathering of additional data for ad-hoc analysis as needed

Qualification

• Bachelor’s degree in Finance, Accounting, Business, Mathematics, Statistics, Economics, Computer Science or any other related discipline or commensurate work experience or demonstrated competence
• Proven experience in financial data analytics, reporting automation, and Power BI tools.

Requirements

• At least 3 – 5 years of financial/business/data analysis experience.
• Experience in audit or logistics industry is a plus.
• Strong understanding of finance principles, datasets and business processes.
• Self-motivated, forward-thinking, resulted orientated and the ability to manage priorities.
• Ability to self-start and self-direct work in an unstructured environment, comfortable dealing with ambiguity.
• Strong analytical skills, curious, meticulous, innovative and resourceful to resolve issues.
• Good business acumen with the ability to synthesize complex data from different source into meaningful insights and actionable information to stakeholders.
• Vocal and confident to voice constructive challenges to business assumptions.
• Good perspective in achieving results both short and long term and be held accountable.
• Strong communications and interpersonal skills in a multicultural environment with a good command of spoken and written English to influence and motivate.
• Eagerness to learn and adapt to new tools, techniques, and technologies in the field of data analysis
• Experience building/applying statistical and/or machine learning solutions to solve business problems and facilitate interactive data visualization.
• Good understanding of data design pattern differences between transactional ERP systems (e.g. SAP) and analytical data warehouses (e.g. Teradata, Snowflake)
• Proficient in data analysis tools (e.g. Excel, SQL) and BI tools (e.g. Power BI, Microsoft Fabric, Tableau)
• Familiarity with scripting or programming languages (e.g. Python, R) for advanced analytics.

Key Results Area

• Deliver timely and seamless execution of projects that align with organizational objectives and needs, meeting the stipulated scope and budget.
• Excellent business collaboration skills and the ability to communicate effectively with a broad and diverse group of stakeholders to ensure stakeholder needs are met.