Senior Manager - Product Analytics

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Skills you'll use

What you'll do

• Experiment Design and Interpretation:
• Lead and design complex experiments, addressing challenges with statistical rigor.
• Interpret results and provide actionable insights to drive business decisions.
• Data Engineering Workflow and Design:
• Partner with stakeholders to ensure data systems and structures are efficient and reliable.
• Reduce turnaround time (TAT) for analytics, feature exploration, and experimentation setup
• Data Science Model Integration:
• Collaborate with data science teams to integrate models into workflows.

Who can apply

• 8–15 years of total professional experience, preferably in Tech, Consulting, or high-scale Analytics organizations.
• 4+ years of people management experience, leading data science, analytics, or operational analytics teams in system-heavy environments.
• Advanced proficiency in SQL and Python — able to drive deep analyses, RCA investigations, and metric instrumentation independently.
• Hands-on experience with Spark or distributed data processing frameworks for scalable analysis.
• Proven ability to design and deploy control systems or feedback loops in collaboration with engineering teams to tune complex algorithms in production.
• Successfully implemented and maintained Data Science models in production, including monitoring and post-deployment tuning.
• Solid foundation in statistical methods, hypothesis testing, and experimental design, especially as applied to system performance and anomaly detection.
• Comfort working with observability and visualization tools — Tableau, Looker, Power BI, or internal metric dashboards like Grafana or Superset.
• Strong record of cross-functional collaboration with engineering, product, SRE, and ML teams to drive system health and platform improvements.
• Demonstrated ability to work through ambiguity, structure diagnostic approaches, and drive data-informed operational decisions.

About InMobi

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