Director Data Science

Lever, Inc.; Bengaluru; On-site; INR 5,500,000 - 9,500,000; Full time

Benefits offered by this job

Experience leading ML initiatives in e

Publications or contributions to open‑

Job summary

Meesho is seeking a Director - Data Science in Bengaluru to lead a high-performance team building production-grade ML systems at scale. You will own the data science roadmap, translate complex business challenges into measurable AI initiatives, and partner with product, engineering, and business leaders to drive growth.

You will mentor 20+ data scientists, set technical direction, ensure model reliability, and foster a culture of experimentation and scientific excellence while delivering impact

Qualifications

• 10+ years of experience in Data Science or Analytics, with at least 6 years of people management.
• Strong research background and knowledge of state of the art in AI/ML.
• Experience managing teams of 20+ data scientists and delivering across cross-functional charters.
• Deep expertise in ML algorithms, experimental design, and performance monitoring.
• Strong coding skills (Python, SQL) and familiarity with Big Data technologies like Spark, Hive, or Redshift.
• Ability to translate business needs into technical solutions, prioritize roadmaps, and estimate effort accurately.
• Strong communication and stakeholder management skills with a bias for action and clarity in execution.
• Strong experience in building large scale AI/ML applications for areas such as recommendations systems, ranking, retrieval, search etc

Responsibilities

• Lead, grow, and mentor a high-performing team of data scientists.
• Own all data science systems and models in your charter - from strategy to deployment and monitoring.
• Collaborate with senior product, engineering, and business leaders to define and prioritize impactful AI/ML initiatives.
• Represent Data Science in senior leadership discussions and clearly communicate technical strategies, investment decisions, trade-offs, and business impact.
• Drive platformization, system architecture decisions, and ML lifecycle improvements across the charter.
• Ensure model scalability, performance, and cost efficiency, while upholding best practices in experimentation and statistical rigor.
• Guide the team in reading and implementing state-of-the-art research, and facilitate build vs. buy decisions.
• Lead RCA for critical production issues and improve system observability, documentation, and service uptime.

Skills

Data science leadership

Team management

ML modeling

Production ML systems

Python

SQL

Communication

Education

Master's degree

PhD preferred

Tools

Spark

Hive

Redshift

Job description

About the Team

Our Data Science team is the Avengers to Meesho's S.H.I.E.L.D . And why not? We are the ones who assemble during the toughest challenges and devise creative solutions, building intelligent systems for millions of our users looking at a thousand different categories of products. We've barely scratched the surface, and have amazing challenges in charting the future of commerce for Bharat.

About the role

Are you a strategic thinker with a passion for solving large-scale problems using data? Do you enjoy mentoring high-performing teams and building ML systems that directly impact millions of users? We're looking for a Director - Data Science to lead a team of skilled data scientists in building intelligent systems that power Meesho's next phase of growth.

In this role, you'll own the data science roadmap for a key business charter, guiding the team through ambiguity and complexity to deliver production-grade ML solutions. You'll work closely with product, tech, and business leaders to translate complex challenges into scalable, measurable, and impactful outcomes. As a people and technical leader, you'll ensure model efficiency, system reliability, and scientific excellence while fostering a culture of innovation, collaboration, and continuous improvement.

What You Will Do

• Lead, grow, and mentor a high-performing team of data scientists..
• Own all data science systems and models in your charter - from strategy to deployment and monitoring.
• Collaborate with senior product, engineering, and business leaders to define and prioritize impactful AI/ML initiatives.
• Represent Data Science in senior leadership discussions and clearly communicate technical strategies, investment decisions, trade-offs, and business impact.
• Drive platformization, system architecture decisions, and ML lifecycle improvements across the charter.
• Ensure model scalability, performance, and cost efficiency, while upholding best practices in experimentation and statistical rigor.
• Guide the team in reading and implementing state-of-the-art research, and facilitate build vs. buy decisions.
• Lead RCA for critical production issues and improve system observability, documentation, and service uptime.

What You Will Need

• Master's degree (PhD preferred) in Machine Learning, Statistics, Computer Science, or a related quantitative field.
• 10+ years of experience in Data Science or Analytics, with at least 6 years of people management experience.

• Strong research background and knowledge of state of art in AI / ML.
• Proven track record of building and deploying ML models in production at scale.
• Experience managing teams of 20+ data scientists and delivering across cross-functional charters.
• Deep expertise in ML algorithms, experimental design, and performance monitoring.Strong coding skills (Python, SQL) and familiarity with Big Data technologies like Spark, Hive, or Redshift.
• Ability to translate business needs into technical solutions, prioritize roadmaps, and estimate effort accurately.
• Strong communication and stakeholder management skills with a bias for action and clarity in execution.
• Strong experience in building large scale AI/ML applications for areas such as recommendations systems, ranking, retrieval, search etc

Bonus Points For

• Experience leading ML initiatives in B2C or e-commerce settings.
• Contributions to internal tools, open-source libraries, or research publications.
• Strong understanding of ML system performance trade-offs - latency, cost, and throughput.
• Top tier research Publications in the areas of AI and ML, especially in recsys, IR and knowledge discovery.