Lead Data Scientist

As a Lead Data Scientist, you will operate at the intersection of advanced machine learning, large-scale data processing, and cross-functional collaboration, building scalable, production-ready solutions that drive significant business value. You will work across multiple business units, tackling Navi's most complex and high-priority challenges, while fostering a culture of technical excellence, continuous innovation, and mentorship within the team. Your contributions will be instrumental in unlocking new opportunities, accelerating growth, and establishing data science as a core strategic asset at Navi.

Responsibilities:

• Lead High-Impact Projects: Oversee and manage end-to-end high-priority data science projects across domains by breaking down complex problems, planning timelines, allocating resources, and ensuring timely, high-quality delivery of results.
• Mentorship and Team Development: Mentor and coach a team of data scientists, fostering a culture of continuous learning, professional growth, and technical excellence. Guide team members in their project work and support their career advancement.
• POC and SOTA Solution Delivery: Rapidly solve complex problems by designing and executing quick POCs using state-of-the-art (SOTA) approaches, and deliver best-in-class ML solutions that create clear differentiation and business impact.
• Strategic Vision and Innovation: Define the strategic roadmap for the team, set technical direction, and champion the development of data-driven solutions for complex business challenges. Ensure alignment with organizational objectives and foster a culture of innovation.
• Cross-Functional Partnership: Build and nurture strong relationships with stakeholders across business, product, and engineering. Identify opportunities, shape strategic initiatives, and drive the successful integration of data science solutions into core business functions.
• Model Quality and Monitoring Excellence: Establish robust metrics and quality standards for evaluating model performance and business impact. Implement and oversee industry-leading systems for model monitoring to ensure reliability, scalability, and long-term value.

Requirements:

• Bachelor's or higher degree in computer science, electrical engineering, or a quantitative field, with a strong research orientation and at least 7 years of relevant experience in data science.
• Deep expertise in modern machine learning techniques, mathematical foundations, and hands-on experience with leading ML frameworks (such as scikit-learn, Keras, TensorFlow, PySpark, MLlib, etc. ).
• Extensive experience with distributed computing platforms and scalable data processing (e. g., Spark).
• Advanced programming skills, preferably in Python, Scala, or similar languages, with a track record of delivering robust, production-grade solutions.
• Proven ability to lead and deliver large-scale machine learning projects end-to-end, from problem definition, data exploration, and modeling to deployment and production monitoring.
• Demonstrated experience in mentoring junior data scientists, including setting technical direction and driving best practices.
• Strong business acumen and the ability to translate complex data-driven insights into actionable strategies that create significant business impact.
• Skilled in designing, executing, and scaling A/B or multivariate experiments to validate and optimize data science solutions.
• Excellent communication and stakeholder management skills, with experience collaborating across business, product, and engineering functions.
• Proven track record of driving innovation and staying current with the latest advancements in machine learning and data science.