Data Scientist

Reposted 10 Days Ago
Be an Early Applicant
Hiring Remotely in IND
Remote
Senior level
Artificial Intelligence • Information Technology • Software
The Role
Lead design and production deployment of end-to-end ML models (PQL scoring, churn, expansion) using MLOps. Build pipelines for dataset/versioning, monitoring, automated retraining, and model registry. Collaborate with Product, Sales, and Data Engineering, own model observability, incident response, dbt data models, and experimentation lifecycle to deliver production-grade analytics.
Summary Generated by Built In

What You Can Expect

Lead the development of a system converting raw telemetry into actionable insights using automation and scalable MLOps principles within a multi-product SaaS environment. Responsibilities include data exploration, model development, deployment, production monitoring, and incident response.

The role focuses on scaling predictive analytics for PQL scoring, expansion modeling, and churn prediction. Collaborate with teams to translate insights into impactful business actions for Sales, Product, and Leadership stakeholders. Deliver a full-lifecycle solution that moves beyond ad hoc analyses to create a robust, production-grade intelligence engine supporting strategic decision-making across the organization.

About the Team

We build data products that power revenue decisions across a multi-product SaaS platform. Our team partners closely with Sales, Product, and Engineering to turn telemetry into action.

Responsibilities

  • Designing and deploying end-to-end ML models — including PQL scoring, churn prediction, and expansion modeling — into production environments with defined latency and accuracy SLAs.

  • Building and maintaining MLOps pipelines covering dataset versioning, feature drift monitoring, automated retraining, and model registry management.

  • Collaborating with Product and Data Engineering teams to establish telemetry schemas, data contracts, and quality validation frameworks, ensuring models train and score using dependable data.

  • Owning model observability by creating dashboards and alerts for performance degradation, prediction drift, and data anomalies — and leading incident response when issues arise.

  • Standardising analytics frameworks by developing reusable dbt data models and owning the full experimentation lifecycle, from A/B test design to ship/no-ship recommendations.

What We're Looking For

  • Demonstrate 6+ years of experience in applied data science or product analytics, or equivalent practical experience.

  • Apply advanced SQL and Python (Pandas, Scikit-learn, Statsmodels, PyTorch or TensorFlow) to solve complex analytical problems.

  • Build, deploy, and monitor ML models in production environments with a focus on reliability and performance.

  • Apply strong foundations in statistics, causal inference, and experimentation design to business problems.

  • Work with telemetry and event-level data to model user behaviour and product engagement.

  • Use MLOps platforms such as MLflow, SageMaker, Vertex AI, or Kubeflow to manage model lifecycles.

  • Apply data quality and observability tools (e.g. Great Expectations, Soda, Monte Carlo) to upstream data pipelines.

  • Leverage LLMs or generative AI techniques to automate insight generation from telemetry data.


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. Click Learn for more information.


About Us
Zoomies help people stay connected so they can get more done together. We set out to build the best collaboration platform for the enterprise, and today help people communicate better with products like Zoom Contact Center, Zoom Phone, Zoom Events, Zoom Apps, Zoom Rooms, and Zoom Webinars.
We’re problem-solvers, working at a fast pace to design solutions with our customers and users in mind. Find room to grow with opportunities to stretch your skills and advance your career in a collaborative, growth-focused environment.

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.


Our interviews are supported by BrightHire, a tool that helps us create a consistent and thoughtful interview experience and may include recordings. Please refer to our candidate privacy statement for more information of how we use your data.

#LI-Remote

Skills Required

  • 6+ years of applied data science or product analytics experience (or equivalent)
  • Advanced SQL skills
  • Advanced Python including Pandas and ML/Stats libraries
  • Experience with Scikit-learn, Statsmodels, PyTorch or TensorFlow
  • Build, deploy, and monitor ML models in production with reliability and performance focus
  • Experience building and maintaining MLOps pipelines (dataset versioning, feature drift monitoring, automated retraining, model registry)
  • Experience with MLOps platforms (MLflow, SageMaker, Vertex AI, or Kubeflow)
  • Foundations in statistics, causal inference, and experimentation design
  • Experience working with telemetry and event-level data to model user behavior
  • Familiarity with data quality and observability tools (Great Expectations, Soda, Monte Carlo)
  • Experience developing reusable dbt data models and owning experimentation lifecycle (A/B test design and analysis)
  • Experience leveraging LLMs or generative AI techniques for insight automation

Zoom Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Zoom and has not been reviewed or approved by Zoom.

  • Fair & Transparent Compensation Compensation is positioned at or above market for many roles, and postings often include clear pay ranges that help set expectations. Market standing among similar-size tech firms reinforces the perception of strong total rewards.
  • Equity Value & Accessibility Equity grants and an ESPP are prominent parts of the package and can materially augment cash compensation. Stock components are framed as a meaningful contributor to overall pay satisfaction.
  • Healthcare Strength Medical plan choice is broad and paired with free dental and vision for employees and dependents, plus robust mental-health resources and disability coverage. These elements position core health benefits as a standout strength.

Zoom Insights

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The Company
HQ: San Jose, CA
11,053 Employees
Year Founded: 2013

What We Do

Bring teams together, reimagine workspaces, engage new audiences, and delight your customers –– all on the Zoom platform you know and love. 💙 Zoomies help people stay connected so they can get more done together. We set out on a mission to make video communications frictionless and secure by building the world’s best video product for the enterprise, but we didn’t stop there. With products like AI Companion, Team Chat, Contact Center, Phone, Events, Rooms, Webinar, and more, we bring innovation to a wide variety of customers, from the conference room to the classroom, from doctor’s offices to financial institutions to government agencies, from global brands to small businesses. We do what we do because of our core value of Care: care for our community, our customers, our company, our teammates, and ourselves. Our global employees help our customers meet happier, communicate better, and create meaningful connections the world over. Zoomies are problem-solvers and self-starters, working hard to get results and moving quickly to design solutions with our customers and users in mind. Here, you’ll work across teams to dig deep into impactful projects that are changing the way people communicate, and find room to grow with opportunities to stretch your skills and advance your career in a diverse, inclusive environment. Learn more about careers at Zoom by visiting our careers site: https://careers.zoom.us/home

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