Senior Data Scientist

Zoom; India; Hybrid; INR 1,800,000 - 2,500,000; Full time

Benefits offered by this job

Comprehensive benefits program

Support for work-life balance

Mentorship opportunities

Job summary

Zoom is seeking an experienced professional for a crucial role in the Revenue Intelligence team, focusing on product analytics and applied data science. The ideal candidate will have over 8 years of experience, with expertise in SQL and Python. Responsibilities include designing telemetry models, managing the MLOps lifecycle, and mentoring junior data scientists. This hybrid position offers a unique opportunity to contribute to strategic decision-making that drives customer growth, retention, and expansion. Comprehensive benefits support work-life balance.

Qualifications

• 8+ years in product analytics or applied data science.
• Expertise in SQL and Python.
• Experience with building, deploying, and monitoring ML models.
• Familiarity with modeling user behavior using telemetry data.
• Solid understanding of statistics and A/B testing frameworks.

Responsibilities

• Designing telemetry models to predict user journey transitions.
• Conducting exploratory data analysis and diagnosing trends.
• Managing the MLOps lifecycle including retraining pipelines.
• Defining batch and real-time inference strategies.
• Maintaining dashboards and response protocols for model performance.
• Building analytics systems and standardizing metric definitions.
• Mentoring junior data scientists and presenting insights to executives.

Skills

SQL

Python

MLOps platforms

Data transformation tools

Business intuition

Education

Bachelor's or Master's in Statistics, Data Science, Computer Science, Economics, or related field

Tools

MLflow

SageMaker

Vertex AI

dbt

Snowflake

Job description

What you can expect

This role involves engineering Zoom's Revenue Intelligence Engine to transform raw telemetry into actionable insights that drive customer growth, retention, and expansion. Responsibilities include building scalable systems for lead scoring, expansion modeling, and churn prediction within a multi-product SaaS environment. Tasks span data exploration, model development, deployment, monitoring, and strategic storytelling. Collaboration with Product and Data Engineering ensures telemetry contracts, reusable analytics frameworks, and production-ready models. Efforts include investigating conversion issues and presenting findings to executives. The work directly influences revenue by supporting Sales, Product, and CS teams with data-driven decision-making tools.

About the Team

This role sits within the Revenue Intelligence team, focused on building the data foundation and ML systems that drive Zoom’s go-to-market strategy. The team partners with Sales, Product, Customer Success, and Data Engineering to ensure that the right signals reach the right people at the right time — from PQL scores surfaced in the GTM stack to experimentation insights delivered to Product leadership.

Responsibilities

• Designing telemetry models to predict user journey transitions and support growth initiatives.
• Conducting exploratory data analysis and diagnosing trends like conversion drops or churn spikes.
• Managing the MLOps lifecycle, including retraining pipelines and model registry oversight.
• Defining batch and real-time inference strategies for model serving architecture.
• Maintaining dashboards, alerts, and incident response protocols for model performance.
• Establishing data validation frameworks and ensuring schema and data quality standards.
• Develop analytics design systems and own experimentation — standardize metric definitions across products, build modular dbt data models, and own the full A/B testing lifecycle from design to ship/no-ship recommendations
• Mentor and communicate at scale — guide junior data scientists, maintain model cards and runbooks, and present findings and business recommendations to VP/C-level stakeholders

What we’re looking for

• 8+ years of experience in product analytics or applied data science with education in Statistics, Data Science, Computer Science, Economics, or a related quantitative field.
• Demonstrate expertise in SQL and Python with advanced querying and data modeling skills.
• Build, deploy, and monitor ML models with a solid foundation in statistics and experimentation.
• Work with telemetry and event data to model user behavior effectively.
• Leverage MLOps platforms like MLflow, SageMaker, or Vertex AI for production environments.
• Utilize data transformation tools such as dbt and Snowflake for analytics workflows.
• Apply business intuition to growth, conversion funnels, and customer lifecycle challenges.
• Develop A/B testing frameworks to inform product and business decisions.
• Communicate insights clearly to stakeholders, including VP and executive-level audiences. Similar

Ways of Working

Our structured hybrid approach is centered around our offices and remote work environments. The work style of each role, Hybrid, Remote, or In-Person is indicated in the job description/posting.

Benefits

As part of our award-winning workplace culture and commitment to delivering happiness, our benefits program offers a variety of perks, benefits, and options to help employees maintain their physical, mental, emotional, and financial health; support work-life balance; and contribute to their community in meaningful ways. Learn for more information.

Our Commitment

At Zoom, we believe great work happens when people feel supported and empowered. We’re committed to fair hiring practices that ensure every candidate is evaluated based on skills, experience, and potential. If you require an accommodation during the hiring process, let us know—we’re here to support you at every step.

If you need assistance navigating the interview process due to a medical disability, please submit an Accommodations Request Form and someone from our team will reach out soon. This form is solely for applicants who require an accommodation due to a qualifying medical disability. Non-accommodation-related requests, such as application follow-ups or technical issues, will not be addressed.

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