About JobTech
JobTech is the world's leading artificial intelligence and big labour data analytics product company that empowers leaders to develop people for new work realities, driven by real labour market needs and individuals' personal aspirations. JobTech is growing rapidly with global big names customers from both private and public sectors.
About the Team
The JobTech team is an enthusiastic bunch obsessed with improving the jobs market by marrying technology and labour market intelligence. We embrace empowerment and appreciate the depth of every member’s area of expertise. We are hands-on dreamers that are willing to invest in projects and people. If you think you should be part of this awesome team looking to scale faster and better, don’t be shy and let us know!
Job Description
As a Data Scientist at JobTech, you will leverage your skills in machine learning, data analytics, and AI to build solutions that enhance our platform and provide real value to our users. In this role, you’ll collaborate closely with internal teams and clients, delivering data-driven insights that inform product decisions and client strategies. You’ll also be directly involved in client calls, where you will present findings, discuss analytical results, and ensure alignment with client objectives.
Key Responsibilities:
- Develop and Implement AI Models: Build and optimize machine learning models, focusing on natural language processing (NLP), recommendation engines, knowledge graphs, and information extraction to drive value for both our platform and clients.
- Cross-functional Collaboration: Work with product managers, engineers, and fellow data scientists to ensure machine learning and analytics solutions are aligned with business goals.
- Prototyping and Experimentation: Continuously experiment with new algorithms and data techniques. Prototype models, iterate, and test their performance to ensure they meet real-world needs.
- Data Integrity & Architecture: Collaborate with data engineers to design and maintain scalable data architectures, pipelines, and analytics systems.
- Model Deployment & Monitoring: Deploy machine learning models into production environments, monitor their performance, and iterate on improvements to enhance results.
- Data Analytics & Insights: Perform in-depth data analytics, turning raw data into actionable insights that inform product decisions and client strategies. Use statistical and machine learning models to identify trends, patterns, and opportunities for product improvement.
- Client Engagement: Participate in client calls to present your data-driven findings and recommendations. Collaborate with clients to understand their needs and ensure our analytics solutions meet their expectations.
Requirements
- Educational Background: Master’s or PhD in Data Science, Computer Science, Engineering, or a related quantitative field.
- Experience: 2+ years of experience in data science or analytics, with a proven track record of delivering machine learning solutions and driving value through data insights.
- Knowledge Graphs Expertise: Solid understanding and experience with knowledge graph representation and applications, particularly in improving information extraction and recommendation engines.
- Data Analytics Expertise: Strong experience in data analytics, including exploratory data analysis, statistical modeling, and delivering insights to business and client stakeholders.
- Client Communication Skills: Ability to communicate complex data insights to non-technical audiences and engage with clients to address their needs.
Technical Skills:
- Advanced proficiency in Python and familiarity with data analysis and machine learning libraries (e.g., pandas, scikit-learn, TensorFlow, PyTorch).
- Experience with SQL and relational databases. Experience with Java is a plus.
- Hands-on experience building and deploying machine learning pipelines.
- Knowledge of cloud platforms (e.g., AWS, GCP) and containerization tools like Docker is advantageous.
Compliance with our strict information security policies is mandatory
- Policy Compliance: Adhere to JobTech's information security policies and procedures.
- Risk Management: Identify, assess, and mitigate security risks to protect sensitive information.
- Incident Response: Participate in the detection, analysis, and response to security incidents.
- Security Training: Attend regular training on information security best practices.
- Data Protection: Ensure the confidentiality, integrity, and availability of JobTech data.
- Regulatory Compliance: Ensure compliance with relevant legal, regulatory, and contractual requirements related to information security.
- Team Collaboration: Work closely with other functional departments to ensure cohesive security measures.
- Confidentiality: Maintain the confidentiality of sensitive information and enforce data protection measures.
- Continuous Improvement: Stay updated on the latest security trends and continuously improve the JobTech's security posture.
