Senior Manager - Product Analytics

InMobi; Bengaluru; On-site; INR 1,800,000 - 3,000,000; Full time

Job summary

InMobi is seeking an Operational Data Scientist to lead experiments, design data systems, and drive analytics across product and platform teams. You will collaborate with engineering, product, and ML squads to translate data into actionable insights and measurable outcomes.

You’ll own metrics, mentor analysts, and ensure production models stay robust, scalable, and aligned with business goals in a fast-moving, privacy-conscious advertising technology environment.

Qualifications

• 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.
• 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.
• Strong strategic and systems thinking mindset — able to reason about interdependent metrics and optimize for system-wide health.

Responsibilities

• Experiment Design and Interpretation: Lead and design complex experiments with statistical rigor and provide actionable insights.
• Data Engineering Workflow and Design: Partner with stakeholders to ensure data systems are efficient and reliable.
• Data Science Model Integration: Collaborate with data science teams to integrate models into workflows and production.
• Proactive and Reactive Analysis: Conduct exploratory data analysis, simulations, and hypothesis testing.
• Health Metrics Design and Implementation: Define, implement, and monitor key performance metrics for platform health.
• Leadership and Collaboration: Liaise between cross-functional teams and mentor analysts.
• Product Impact Tracking: Design analyses to monitor product impact and align with business objectives.

Skills

SQL

Python

Spark

Experiment design

Data analysis

Model deployment

Statistical methods

Observability tools

Cross-functional collaboration

Systems thinking

Tools

Tableau

Looker

Power BI

Grafana

Superset

Job description

InMobi Advertisingis a global technology leader helping marketers win the moments that matter. Our advertising platform reaches over 2 billion people across 150+ countries and turns real-time context into business outcomes, delivering results grounded in privacy-first principles. Trusted by 30,000+ brands and leading publishers, InMobi is where intelligence, creativity, and accountability converge. By combining lock screens, apps, TVs, and the open web with AI and machine learning, we deliver receptive attention, precise personalization, and measurable impact.

Through Glance AI,we are shaping AI Commerce, reimagining the future of e-commerce with inspiration-led discovery and shopping. Designed to seamlessly integrate into everyday consumer technology, Glance AI transforms every screen into a gateway for instant, personal, and joyful discovery. Spanning diverse categories such as fashion, beauty, travel, accessories, home décor, pets, and beyond, Glance AI delivers deeply personalized shopping experiences.With rich first-party data and unparalleled consumer access, it harnesses InMobi’s global scale, insights, and targeting capabilities to create high impact, performance driven shopping journeys for brands worldwide.

Recognized as a Great Place to Work, and by MIT Technology Review, Fast Company’s Top 10 Innovators, and more, InMobi is a workplace where bold ideas create global impact. Backed by investors including SoftBank, Kleiner Perkins, and Sherpalo Ventures, InMobi has offices across San Mateo, New York, London, Singapore, Tokyo, Seoul, Jakarta, Bengaluru and beyond.

AtInMobi Advertising, you’ll have the opportunity to shape how billions of users connect with content, commerce, and brands worldwide. To learn more, visit www.inmobi.com

Why you should join us?

At our core, we believe in the power of data to drive smarter decisions and transform operations. As an Operational Data Scientist, you'll be at the forefront of this mission—leading initiatives that streamline business processes, accelerate time to insight, and align analytics with strategic goals.

You’ll work in an environment that values rigor in experimental design, seamless model integration, and impactful operational analytics. We’re not just looking for technical talent—we want a strategic thinker and a collaborative leader who thrives at the intersection of data, business, and execution.

If you're passionate about solving complex problems, influencing high-stakes decisions, and driving measurable outcomes, this is the opportunity to make your mark. Join us and be part of a team that turns data into action—and action into impact.

What will you be doing?

1. Experiment Design and Interpretation:

• Lead and design complex experiments, addressing challenges with statistical rigor.
• Interpret results and provide actionable insights to drive business decisions.

2. 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

3. Data Science Model Integration:

• Collaborate with data science teams to integrate models into workflows.
• Define success metrics, identify inefficiencies, and leverage model outputs to enhance operations.

4. Proactive and Reactive Analysis:

• Conduct exploratory data analysis, simulations, and hypothesis testing.
• Provide strategic support and actionable insights to address business challenges.

5. Health Metrics Design and Implementation:

• Define, implement, and monitor key performance metrics to assess platform performance and user behavior.

6. Leadership and Collaboration:

• Serve as a liaison between cross-functional teams, advocating for data-driven decisions.
• Mentor analysts and promote a culture of analytics within the organization.

7. Product Impact Tracking:

• Design and implement analyses to monitor product impact.
• Ensure alignment of analytics initiatives with broader business objectives.

What are we looking for?

Skills and Attributes:

• 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.
• Strong strategic and systems thinking mindset — able to reason about interdependent metrics and optimize for system-wide health.

The InMobi Culture

At InMobi, culture isn’t a buzzword; it's an ethos woven by every InMobian, reflecting our diverse backgrounds and experiences.

We thrive on challenges and seize every opportunity for growth. Our core values — thinking big, being passionate, showing accountability, and taking ownership with freedom — guide us in every decision we make.

We believe in nurturing and investing in your development through continuous learning and career progression with our InMobi Live Your Potential program.

InMobi is proud to be an Equal Employment Opportunity employer and is committed to providing reasonable accommodations to qualified individuals with disabilities throughout the hiring process and in the workplace.

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