Job Description
Job Summary
- To lead and manage a high performing team of data scientists and machine learning engineers to continuously deliver results
- To manage the entire lifecycle of data science products/portfolio and drive the development of new machine learning capabilities tandem with delivering business value using advanced analytics
Key Responsibilities:
Leadership & Team Management:
- Lead, mentor, and inspire a team of data scientists, providing guidance on best practices in machine learning, statistical modeling, and data-driven decision-making.
- Facilitate career development and foster a culture of continuous learning and experimentation within the team.
Product Management:
- Collaborate with business development, product managers, and other stakeholders to enhance existing data science products.
- Actively engage in product lifecycle management, ensuring alignment with business objectives and customer needs.
- Oversee the deployment and maintenance of machine learning models in production, ensuring robustness and scalability.
Solution Innovation & Development:
- Design and build new data-driven products and services, leveraging machine learning, AI, and advanced analytics to meet evolving business demands.
- Explore innovative applications of data science to create additional value for our platform.
- Infuse machine learning capabilities into operational processes, improving efficiency and accuracy across workflows.
Collaboration & Cross-Functional Partnership:
- Work closely with business development teams to explore new opportunities for data solutions, acting as the technical counterpart to foster data-driven partnerships.
- Collaborate with product managers to define technical requirements for new features and enhancements, ensuring seamless integration of data science solutions.
Research & Development:
- Stay up to date with the latest advancements in machine learning, data engineering, and AI technologies.
- Lead the R&D efforts on emerging techniques such as natural language processing, reinforcement learning, and predictive modeling, ensuring continuous improvement in product offerings.
Performance Monitoring & Optimization:
- Establish and track key performance indicators (KPIs) for all data science initiatives, ensuring measurable impact on business growth and operational efficiency.
- Drive continuous improvement in the performance of deployed models, optimizing for speed, accuracy, and interpretability.
- Drive MLOPS best practices and Infrastructure improvement for all ML/DS initiatives.
Academic Qualification(s):
- Bachelor's degree in Computer Science, Engineering, or a related field
Professional Qualification(s):
Experience (Number of relevant years):
- Minimum of 7 years in Data Science, Machine Learning and Advanced analytics preferably from the fintech, telco or banking sectors.
- 2-3 years leading junior data scientists
- Proven experience in designing, developing, and deploying data science products in production environments.