Data Science Manager

7 days ago

Bengaluru, Karnataka, India HyreSnap Full time

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.

(ref:hirist.tech)

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