Data Science Manager - Machine Learning Models

We're looking for a Data Science Manager 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.

Responsibilities :

- Lead, grow, and mentor a high-performing team of data scientists and ML engineers.

- 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 DS initiatives.

- 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.

Requirements :

- Master's degree (PhD preferred) in Machine Learning, Statistics, Computer Science, or a related quantitative field.

- 9+ years of experience in Data Science, with at least 1-3 years of people management experience.

- Proven track record of building and deploying ML models in production at scale.

- Experience managing teams of 4+ data scientists/engineers 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.