Head of Data Science at Interswitch November, 2024

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.