Manager - Data Science

As a Manager of Data Science, you'll drive the strategy, execution, and impact of data science across Navi's high-growth businesses. You will lead a team of top-tier data scientists, shaping models and solutions that power critical business functions—from lending and collections to UPI and ads. This role goes beyond technical depth; you're expected to combine sharp analytical thinking with business-first decision-making, drive cross-functional collaboration, and establish scalable systems that deliver measurable value. If you're excited about using data science to solve real-world problems at scale, this is the opportunity to make a meaningful impact.

The core responsibilities for the job include the following:

Lead and Develop a High-Impact Team:

• Manage, mentor, and grow a team of data scientists.
• Foster a culture of learning and professional development.
• Guide project execution and support career progression.
• Own performance reviews, compensation, and leave management.

Strategic Vision and Team Performance:

• Set clear goals and expectations.
• Regularly assess team performance and alignment.
• Provide technical leadership and direction.

Cross-Functional Leadership:

• Build strong relationships with business, product, and engineering.
• Act as a strategic partner in initiatives.
• Drive implementation of data science solutions.

Model Quality and Monitoring Excellence:

• Define metrics and quality standards.
• Oversee monitoring and alerting systems.
• Ensure reliability, scalability, and impact.

Drive Cross-Functional Data Science Initiatives:

• Lead initiatives on monitoring, cost reduction, and best practices.
• Promote strong code management and documentation.

Planning and Strategic Initiatives:

• Lead planning processes (quarterly, annual, long-term).
• Ensure project prioritization aligns with strategy.

Opportunity Identification and Value Creation:

• Identify high-value opportunities with business and product.
• Develop innovative solutions that drive outcomes.

Requirements:

• Master's or bachelor's degree in computer science, electrical engineering, mathematics, economics, or another quantitative discipline.
• Strong research-oriented mindset and at least 9+ years of experience in data science, advanced analytics, or related fields.
• Strong business acumen and ability to partner with business, product, and engineering teams.
• Deep expertise in statistics, machine learning, deep learning, and optimization algorithms.
• Proven ability to design, execute, and scale A/B experiments to validate and optimize data science solutions across varied business contexts.
• Advanced programming skills in Python and PySpark.
• Strong track record in data pipelines, feature engineering, and scalable workflows.
• Familiarity with tools and libraries like pandas, scikit-learn, TensorFlow, PyTorch, SQL, and Scala, plus production-grade deployment using Docker, Databricks, and Kubernetes.
• Experience in developing, implementing, and monitoring large-scale ML systems.
• Demonstrated leadership in managing projects and cross-functional teams.
• Experience in people management, team development, and enforcing technical best practices.