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.

Experience
7-11 yrs