Intercom is the AI Customer Service company on a mission to help businesses provide incredible customer experiences.

Our AI agent Fin, the most advanced customer service AI agent on the market, lets businesses deliver always-on, impeccable customer service and ultimately transform their customer experiences for the better. Fin can also be combined with our Helpdesk to become a complete solution called the Intercom Customer Service Suite, which provides AI enhanced support for the more complex or high touch queries that require a human agent.

What's the Opportunity?

The Research, Analytics & Data Science (RAD) team turns insight into action. We uncover customer, product, and business insights and translate them into tools and decision systems embedded directly into GTM workflows.

AI has unlocked an entirely new generation of internal tools for our GTM teams. We’re evolving from static dashboards to LLM and agent-powered workflows that do the work: auto-researching accounts, summarizing prior interactions, drafting personalized outreach, flagging renewal risk, and assembling decks and docs - enabling Sales and Success to focus on high-value conversations.

What Will I Be Doing?

• Design, evaluate, and ship AI-powered internal tools for GTM use cases - including account research & summaries, next-best-action recommendations, renewal propensity, pipeline risk detection, QBR/autobrief generation, and post-call summarization & follow-ups.
• Work end-to-end: Own the full lifecycle, from problem definition and data modeling to building production-ready tools, including writing Python backends and React frontends.
• Prototype fast, ship to learn: Rapidly build with users, then productionize quickly to iterate and deliver impact.
• Instrument for adoption and outcomes: Define success through real usage and measurable business impact (e.g., improved win rate, conversion, expansion).
• Evangelize and enable: Document playbooks, run enablement sessions, and help leaders operationalize new tooling across teams.

What Skills Do I Need?

• Proven track record of applied data science with measurable GTM impact - you’ve shipped models or tools that moved metrics like conversion, cycle time, or retention.
• LLM/ML application experience - familiarity with RAG, prompt and tool design, vector search, evals and have leveraged AI for development.
• Excellent SQL skills and fluency in Python or R, with experience applying analytical and statistical methods to business problems.
• Experience with orchestration tools (e.g., DBT, Airflow) for deploying reliable data workflows.
• Strong communication and empathy - ability to translate complex data concepts for non-technical stakeholders.
• Collaborative product mindset - comfort working closely with Sales and Success teams to turn ambiguity into clear deliverables.

Benefits

We are a well-treated bunch, with awesome benefits! If there’s something important to you that’s not on this list, talk to us!

• Competitive salary and equity in a fast-growing start-up
• We serve lunch every weekday, plus a variety of snack foods and a fully stocked kitchen
• Regular compensation reviews - we reward great work
• Peace of mind with life assurance, as well as comprehensive health and dental insurance for you and your dependents
• Open vacation policy and flexible holidays so you can take time off when you need it
• Paid maternity leave, as well as 6 weeks paternity leave for fathers, to let you spend valuable time with your loved ones
• MacBooks are our standard, but we’re happy to get you whatever equipment helps you get your job done

Policies

Intercom has a hybrid working policy. We believe that working in person helps us stay connected, collaborate easier and create a great culture while still providing flexibility to work from home. We expect employees to be in the office at least three days per week.

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We're looking for a Senior Data Scientist to join our Research, Analytics & Data Science (RAD) team. The RAD team turns insight into action by uncovering customer, product, and business insights and translating them into tools and decision systems embedded directly into GTM workflows.

AI has unlocked an entirely new generation of internal tools for our GTM teams. We're evolving from static dashboards to LLM and agent-powered workflows that do the work: auto-researching accounts, summarizing prior interactions, drafting personalized outreach, flagging renewal risk, and assembling decks and docs - enabling Sales and Success to focus on high-value conversations.

Responsibilities:

• Design, evaluate, and ship AI-powered internal tools for GTM use cases - including account research & summaries, next-best-action recommendations, renewal propensity, pipeline risk detection, QBR/autobrief generation, and post-call summarization & follow-ups.

• Work end-to-end: Own the full lifecycle, from problem definition and data modeling to building production-ready tools, including writing Python backends and React frontends.

• Prototype fast, ship to learn: Rapidly build with users, then productionize quickly to iterate and deliver impact.

• Instrument for adoption and outcomes: Define success through real usage and measurable business impact (e.g., improved win rate, conversion, expansion).

• Evangelize and enable: Document playbooks, run enablement sessions, and help leaders operationalize new tooling across teams.

Requirements:

• Proven track record of applied data science with measurable GTM impact - you've shipped models or tools that moved metrics like conversion, cycle time, or retention.

• LLM/ML application experience - familiarity with RAG, prompt and tool design, vector search, evals and have leveraged AI for development.

• Excellent SQL skills and fluency in Python or R, with experience applying analytical and statistical methods to business problems.

• Experience with orchestration tools (e.g., DBT, Airflow) for deploying reliable data workflows.

• Strong communication and empathy - ability to translate complex data concepts for non-technical stakeholders.

• Collaborative product mindset - comfort working closely with Sales and Success teams to turn ambiguity into clear deliverables.

Benefits:

• Competitive salary and equity in a fast-growing start-up

• Unlimited access to Claude Code and best-in-class AI tools; experimentation & building is encouraged & celebrated.

• We serve lunch every weekday, plus a variety of snack foods and a fully stocked kitchen

• Regular compensation reviews - we reward great work

• Peace of mind with life assurance, as well as comprehensive health and dental insurance for you and your dependents

• Open vacation policy and flexible holidays so you can take time off when you need it

• Paid maternity leave, as well as 6 weeks paternity leave for fathers, to let you spend valuable time with your loved ones

• MacBooks are our standard, but we're happy to get you whatever equipment helps you get your job done

Policies:

• Intercom has a hybrid working policy. We believe that working in person helps us stay connected, collaborate easier and create a great culture while still providing flexibility to work from home. We expect employees to be in the office at least three days per week.

• We have a radically open and accepting culture at Intercom. We avoid spending time on divisive subjects to foster a safe and cohesive work environment for everyone. As an organization, our policy is to not advocate on behalf of the company or our employees on any social or political topics out of our internal or external communications. We respect personal opinion and expression on these topics on personal social platforms on personal time, and do not challenge or confront anyone for their views on non-work related topics. Our goal is to focus on doing incredible work to achieve our goals and unite the company through our core values.

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San Francisco

Employment Type

Full time

Department

Data Science

Compensation

• $347K – $490K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

More details about our benefits are available to candidates during the hiring process.

This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.

About the Team

The Strategic Finance team at OpenAI plays a critical role in shaping the company’s long-term trajectory. We partner closely with Product, Engineering, and Go-to-Market teams to inform high-stakes decisions through rigorous data science and economic modeling.

As part of our expanding Data Science function, we’re building a best-in-class forecasting capability to drive real-time, data-driven decision-making across user growth, revenue, compute infrastructure, and more.

We are developing a scalable forecasting platform to help us understand and anticipate business dynamics in an increasingly complex, usage-based world. Our models are foundational to planning, pricing, operational efficiency, and growth strategy — supporting key investment decisions and unlocking OpenAI’s full potential.

About the Role

We’re looking for a hands-on technical leader to build and lead a small but mighty team of applied data scientists and ML engineers to develop forecasting capabilities and platforms from the ground up.

Your team will be responsible for building and scaling robust, interpretable, and production-ready forecasting systems. These models will power critical business decisions by predicting core metrics such as DAU/WAU, revenue, compute consumption, and profitability.

You will work closely with Strategic Finance leaders to integrate these scalable forecasting capabilities into their operational rhythms and collaborate with the Growth team to forecast key KPIs.

This is a highly cross-functional role that requires technical excellence, strong product intuition, and business acumen. You’ll collaborate with various partners to operationalize forecasting insights, influence company-wide strategy, and build foundational forecasting capabilities at OpenAI.

This role is based in San Francisco, CA. We follow a hybrid work model of three days in the office per week and offer relocation assistance to new employees.

In this role, you will:

• Build and manage a world-class team of applied data scientists and ML engineers to develop forecasting platforms at scale.
• Design and own the roadmap for the forecasting platform in partnership with cross-functional stakeholders.
• Collaborate closely with Strategic Finance teams to ensure forecasts are well integrated into planning processes, and executive decision-making.
• Work closely with cross-functional partners to help them adopt scientific, automated forecasting solutions.
• Own the end-to-end modeling lifecycle, including scoping, feature engineering, model development and prototyping, experimentation, deployment, monitoring, and explainability.
• Research and evaluate emerging tools and techniques in the forecasting space.
• Translate technical outputs into business-aligned recommendations and decision frameworks.

You might thrive in this role if you have:

• Extensive experience building production-ready models for time series applications.
• Proven track record of building adjustable and explainable forecast models for multiple planning cycles.
• 10+ years of applied data science & engineering experience, with deep hands-on expertise in forecasting and predictive modeling.
• Demonstrated experience with model monitoring, debugging, and long-term maintenance in production environments.
• Excellent communication and storytelling skills — able to simplify complexity and influence executive stakeholders.
• Team leadership experience with a track record of building high-performing, engaged teams.
• An advanced degree (MS or PhD) in a quantitative field (e.g., Statistics, Computer Science, Economics, Operations Research).
• A self-directed, intellectually curious mindset and comfort leading ambiguous projects from 0→1.
• The ability to thrive in a dynamic environment — flexible, resourceful, and willing to do what it

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