# Director Data Science at Meesho Director Data Science at Meesho in Bangalore, Karnataka. On-site, full-time. Posted August 4, 2026. - Company: Meesho - Location: Bangalore, Karnataka - Workplace: On-site - Job type: Full-time - Experience: 10+ years - Posted: 2026-08-04 - Apply: https://jobs.lever.co/meesho/64821526-2485-4a76-9198-610ee3938bb1/apply - Source: https://jobmagic.ai/jobs/director-data-science-meesho-7gk5e3 ## 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.