$200K – $300K/yr
Pay vs market · Bottom quarter
This job's pay ($185,000 a year at the midpoint) is higher than about 10% of 50 salary-listed Member of Technical Staff jobs in New York in the last 12 months; their median is $210,000.
Role overview
Job description
Profound is the fastest-growing AI marketing platform, used by 15% of the Fortune 500 including Comcast, Estée Lauder, and Walmart, and innovators like Ramp, MongoDB, and Figma. It is where marketing teams do the work: research, briefs, content, campaigns, reporting, all in one place, alongside agents that carry the load with them. Built on 2B+ real user prompts and growing, Profound’s data shows you what people ask AI and what the models say back. Profound's AI Marketer joins that data with deep context about our customers to find the opportunities worth acting on, and then puts agents to work: automating reporting, drafting content, auditing pages for readability, running competitive research. It measures what works and gets better every day. As a Data Scientist, you will map every human and AI interaction to help brands turn AIs into their strongest advocates. You will build predictive models, develop sampling techniques, and optimize brand visibility in AI-driven search, such as ChatGPT and Perplexity. Your work will directly impact how businesses shape their presence in the generative AI era. What you’ll do Develop and refine predictive models to analyze and forecast AI-driven search behavior Design sampling and data classification techniques to improve AI-driven brand insights Leverage LLMs and NLP to extract meaningful insights from unstructured text data Work with large datasets, ensuring efficiency in querying, cleaning, and classification Design and conduct A/B tests or other experimentation frameworks to measure impact Collaborate with the founding team to turn complex data insights into actionable business strategies Who you are 3 or more years of advanced analytics experience in technology, marketing, or advertising Proficient in Python, R, and SQL, with hands-on experience querying and analyzing large datasets Expertise in data sampling techniques, including stratified sampling, bootstrapping, and extrapolation Strong background in predictive modeling and applying machine learning techniques to estimate event frequency Deep understanding of large language models, their limitations, and real-world applications Passionate about staying on top of AI research, especially in multi-modal AI and LLM advancements Comfortable in a fast-moving, high-performance startup environment Location This is an on-site role based in our NYC or SF office, designed for builders who thrive on speed, iteration, and meaningful impact. We are happy to support visa sponsorship for qualified international candidates. For this role, the expected base salary range is $140,000 to $260,000 (NYC and SF). Comp may vary by location. Profound’s total compensation package is designed to be competitive and includes base salary, equity, and a full range of benefits and perks. Final compensation will depend on factors such as your skills, experience, qualifications, and location, and will be determined during the interview process. Our recruiting team will share more details about the full compensation package and benefits as you move through hiring. Note: All official communication from Profound will come from a @tryprofound.com email address. If you're contacted by anyone using a different domain, please disregard and report it as spam.
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About this listing
- Source: Profound's official careers site · still listed there on 11 Nov 2026
- Posted 24 Jul 2025
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Role market pulse
How Member of Technical Staff demand looks in United States
Live jobs
323
Posted 30d
298
30d movement
+1652.9%
Remote share
25.1%
Salary listed
90.4%
Salary trend 1Y
Not enough history
What they are looking for
Skills & requirements
Qualification
We are happy to support visa sponsorship for qualified international candidates
Department · Data
Hiring company
Profound
View the company profile, current openings and hiring details.
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