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

Experience
9-13 yrs