Data Scientist

Profound

San Francisco (CA)

On-site

USD 140,000 - 260,000

Full time

14 days+

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Job summary

Profound is hiring a Data Scientist in San Francisco to build predictive models and optimize AI-driven brand visibility. The ideal candidate has 3+ years of advanced analytics experience, strong skills in Python, R, and SQL, and a passion for AI research. Responsibilities include developing predictive models, working with large datasets, and collaborating with teams to turn data insights into strategies. This on-site role offers a base salary between $140,000 and $260,000, with a competitive compensation package.

Qualifications

  • 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 and bootstrapping.
  • Strong background in predictive modeling and applying machine learning techniques.

Responsibilities

  • Develop and refine predictive models to analyze 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.
  • Collaborate with the founding team to turn complex data insights into actionable business strategies.

Skills

Predictive modeling
Python
R
SQL
Data sampling techniques
Machine learning
Natural Language Processing (NLP)

Job description

Profound is on a mission to help companies understand and control their AI presence. 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.

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