Data Scientist, B2B Demand Generation, Growth & Measurement
OpenAI is hiring a Data Scientist, B2B Demand Generation, Growth & Measurement for a remote role open to applicants in United States. It pays $293k-$385k a year and Level rates it ; you can apply on OpenAI.
Level's read on this job
- Uses AI ●●○○ is how Level rates this data scientist role: an ordinary role that requires AI tools.
- Pay on this posting starts 76% higher than the typical data scientist posting on Level.
- This is listed as a remote role.
- The posting mentions LLMs, AI research and data science among its tools and skills.
- OpenAI has 795 other open roles on Level.
AI in this role
Lead data science and measurement for B2B demand generation, leveraging experimentation and AI-native decision workflows.
Job Description: Data Scientist, B2B Demand Generation, Growth & Measurement
About the Role
We are hiring a Data Scientist to lead measurement, experimentation, and decision science for B2B marketing demand generation. You will help us understand which marketing investments create incremental demand, qualified pipeline, and revenue and how to scale them efficiently.
Our mandate is to build a rigorous, full-funnel view of how B2B marketing creates demand and moves prospects from awareness and engagement to qualified opportunities, closed-won revenue, and expansion. You will shape how we measure marketing impact and influence across channels, campaigns, audiences, and account segments.
In this role, you will partner closely with B2B Marketing, Demand Generation, Growth, Sales, RevOps, Finance to connect marketing activity to qualified pipeline, customer acquisition, and efficient revenue growth.
What You’ll Do
Define north-star, leading, and guardrail metrics for B2B demand generation, including account engagement, qualified leads and opportunities, sourced and influenced pipeline, conversion rates, pipeline velocity, and incremental ARR.
Design and execute measurement and experimentation strategies across channels and campaigns, using randomized tests, audience or geographic holdouts, lift studies, quasi-experimental methods, and other causal approaches suited to long B2B sales cycles.
Analyze channel, audience, campaign, creative, content, landing-page, and account-segment performance to identify the drivers of qualified demand, funnel conversion, pipeline quality, and incremental revenue.
Partner with Marketing, Sales, RevOps, Finance, Product, and Engineering to improve instrumentation, campaign taxonomy, CRM data quality, lead-to-account matching, and the operating cadence for acting on measurement insights.
Build AI-native measurement and decision-support workflows, using LLMs and agents to synthesize campaign performance, surface growth opportunities, and help marketers act on evidence at scale.
What We’re Looking For
10+ years in a quantitative role such as Data Science, B2B Demand Gen Marketing Science, Growth Analytics, Decision Science, with meaningful experience supporting B2B marketing, demand generation, pipeline growth, or enterprise and SMB go-to-market motions.
Deep expertise in experimentation, causal inference, and applied statistics, including incrementality testing and measurement strategies for multi-touch marketing journeys, limited observability, and long or heterogeneous sales cycles.
Strong technical fluency in SQL and Python, with experience joining and analyzing marketing-platform, web analytics, product, CRM, account, opportunity, and revenue data to produce reliable business insights.
Proven ability to translate analysis into marketing decisions, including channel and audience prioritization, campaign optimization, funnel improvements, budget allocation, forecasting, and go-to-market strategy.
Strong business judgment and a bias toward action.
Strong understanding of B2B funnel mechanics, account-based buying journeys, sales handoffs, lead and opportunity qualification, attribution tradeoffs, instrumentation, and the relationship between marketing investment, pipeline, and revenue.
Excellent communication and cross-functional partnership. You can influence marketers, sales and finance leaders, data scientists, product managers, and engineers with clear recommendations, credible evidence, and transparent tradeoffs.
AI-native mindset and hands-on experience using LLMs, agents, and modern AI tools to automate analysis, accelerate experimentation, and build scalable decision-support workflows.
About OpenAI
OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.
Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.
To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.
We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.
OpenAI Global Applicant Privacy Policy
At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
How we rate this
Data Scientist, B2B Demand Generation, Growth & Measurement at OpenAI rates 45 out of 100 for how much of the daily work is AI. That makes it Uses AI (AI Level 2 of 4). The level is about AI in the job, not seniority.
Uses AI. An ordinary role that requires AI tools.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in data scientist jobs at this level
Pay
- This job starts at
- $293k
- Typical data scientist job
- $166k
This posting starts 76% above the typical data scientist job. See data scientist jobs
Questions you could be asked
- Tell me about a research question you investigated. What did you find?
- Tell me about a project where data science was part of your work. What did you do?
- Tell me about a project where experimentation was part of your work. What did you do?
- Tell me about a project where causal inference was part of your work. What did you do?
- Tell me about a project where analytics was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: AI Research, Data Science, Experimentation, Causal Inference, and Analytics. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Put the AI tool in a bullet point about what you did, not just in a skills list. This role treats it as a required part of the job.
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