Director Data Science

Meesho

Bengaluru

On-site

INR 4,000,000 - 6,000,000

Full time

24 hours ago
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Job summary

Meesho seeks a Director - Data Science to guide a high-caliber team and own the data science roadmap powering Meesho's next growth phase. You will translate complex challenges into scalable ML solutions, collaborating closely with product, tech, and business leaders to deliver measurable impact.

You will drive the platformization of AI initiatives, ensure model efficiency and reliability, and foster a culture of experimentation and innovation across the data science function.

Qualifications

  • Master's degree (PhD preferred) in ML, Stats, CS or related field.
  • 10+ years of Data Science or Analytics experience.
  • 6+ years of people management experience.
  • Proven track record in leading teams of 20+ data scientists.
  • Strong coding skills in Python and SQL.
  • Deep expertise in ML algorithms and experimentation.
  • Experience deploying ML models in production at scale.
  • Experience with large-scale recommender systems and retrieval.
  • Familiarity with Spark, Hive, Redshift and Big Data tools.
  • Excellent communication and stakeholder management.

Responsibilities

  • Lead and mentor a high-performing data science team.
  • Own data science systems from strategy to deployment and monitoring.
  • Collaborate with product, engineering, and business leaders to prioritize AI/ML initiatives.
  • Communicate technical strategies and trade-offs to senior leadership.
  • Drive platformization and ML lifecycle improvements across the charter.
  • Ensure model performance, cost-efficiency, and observability.
  • Guide adoption of state-of-the-art research and build-vs-buy decisions.
  • Lead root-cause analysis for production issues and improve observability.

Skills

Data Science Leadership
People Management
Python
SQL
Big Data
ML Systems
Experimentation
System Design
Recommender Systems
AI/ML

Education

Master's degree
PhD preferred
ML/Statistics/CS

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 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.
Bonus Points For
  • 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-the-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
    • 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.
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