What will you be doing?
 1. Experiment Design and Interpretation:

<ul>
<li>Lead and design complex experiments, addressing challenges with statistical rigor.</li>
</ul>

<ul>
<li>Interpret results and provide actionable insights to drive business decisions.</li>
</ul>
2. Data Engineering Workflow and Design:

<ul>
<li>Partner with stakeholders to ensure data systems and structures are efficient and reliable.</li>
</ul>

<ul>
<li>Reduce turnaround time (TAT) for analytics, feature exploration, and experimentation setup</li>
</ul>
3. Data Science Model Integration:

<ul>
<li>Collaborate with data science teams to integrate models into workflows.</li>
</ul>

<ul>
<li>Define success metrics, identify inefficiencies, and leverage model outputs to enhance operations.</li>
</ul>
4. Proactive and Reactive Analysis:

<ul>
<li>Conduct exploratory data analysis, simulations, and hypothesis testing.</li>
</ul>

<ul>
<li>Provide strategic support and actionable insights to address business challenges.</li>
</ul>
5. Health Metrics Design and Implementation:

<ul>
<li>Define, implement, and monitor key performance metrics to assess platform performance and user behavior.</li>
</ul>

6. Leadership and Collaboration:

<ul>
<li>Serve as a liaison between cross-functional teams, advocating for data-driven decisions.</li>
</ul>

<ul>
<li>Mentor analysts and promote a culture of analytics within the organization.</li>
</ul>
7. Product Impact Tracking:

<ul>
<li>Design and implement analyses to monitor product impact.</li>
</ul>

<ul>
<li>Ensure alignment of analytics initiatives with broader business objectives.</li>
</ul>
 What are we looking for? Skills and Attributes:

<ul>
<li>8–15 years of total professional experience, preferably in Tech, Consulting, or high-scale Analytics organizations.</li>
</ul>

<ul>
<li>4+ years of people management experience, leading data science, analytics, or operational analytics teams in system-heavy environments.</li>
</ul>

<ul>
<li>Advanced proficiency in SQL and Python — able to drive deep analyses, RCA investigations, and metric instrumentation independently.</li>
</ul>

<ul>
<li>Hands-on experience with Spark or distributed data processing frameworks for scalable analysis.</li>
</ul>

<ul>
<li>Proven ability to design and deploy control systems or feedback loops in collaboration with engineering teams to tune complex algorithms in production.</li>
</ul>

<ul>
<li>Successfully implemented and maintained Data Science models in production, including monitoring and post-deployment tuning.</li>
</ul>

<ul>
<li>Solid foundation in statistical methods, hypothesis testing, and experimental design, especially as applied to system performance and anomaly detection.</li>
</ul>

<ul>
<li>Comfort working with observability and visualization tools — Tableau, Looker, Power BI, or internal metric dashboards like Grafana or Superset.</li>
</ul>

<ul>
<li>Strong record of cross-functional collaboration with engineering, product, SRE, and ML teams to drive system health and platform improvements.</li>
</ul>

<ul>
<li>Demonstrated ability to work through ambiguity, structure diagnostic approaches, and drive data-informed operational decisions.</li>
</ul>

<ul>
<li>Strong strategic and systems thinking mindset — able to reason about interdependent metrics and optimize for system-wide health. </li>
</ul>

Data Sciences

India

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.

Data Sciences · Thurahalli

Job highlights

Skillset required

Job Description

Job Description for Data Sciences

More at Inmobi