Principal Data Scientist

We're looking for a Principal Data Scientist 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.
• 8+ years of experience in data science or analytics, with at least 2-3 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.

Bonus Points For:

• Experience leading ML initiatives in B2C or e-commerce settings.
• Contributions to internal tools, open-source libraries, or research publications.
• Experience in personalization, recommendations, ranking, or supply chain ML problems.
• Strong understanding of ML system performance trade-offs: latency, cost, and throughput