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Open nowPosted 63 days ago

Senior Data Scientist

FlightStory36 open roles

Pay
$185,000 a year
Where
Los Angeles, United States
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Your applicationOpen nowSenior Data ScientistFlightStory · Los Angeles, United States

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The clock on this job

Early applications get read.

7.9% of postings close within 7 days. Measured by our own scanner across the market. FlightStory postings stay open a median of 1 days.

Share of postings closed within
  1. 1.6%1 day
  2. 3.6%3 days
  3. 7.9%7 days
  4. 14.9%14 days
  5. 34.2%30 days
This job: posted 63 days ago

FlightStory median: 1 days open

The posting

SENIOR DATA SCIENTIST

COMPANY: STEVEN.COM

REPORTING TO: HEAD OF DATA INTELLIGENCE

LOCATION: LOS ANGELES

SALARY: UP TO $185,000

ABOUT STEVEN.COM

Steven.com is building the operating system for the billion-dollar creator economy. Creators are held back by fragmented distribution, rented audiences, and technology that wasn't built for them. Steven.com is the unlock — the end-to-end Operating System designed to empower, grow, and scale what is irreplaceably human.

We work across four interconnected pillars: Creator Media (reach, influence, trust), Creator Community (turning audiences into connected tribes), Creator Ventures (infrastructure for creators to build and back aligned businesses), and Creator Technology & Data Intelligence - the proprietary data suite that fuels the entire flywheel.

Powering all of it is our Innovation and Technology Organisation (ITO) - Steven.com's founding technical engine, operating in stealth mode to build the data and AI infrastructure underpinning our next stage of growth. Data Intelligence sits at the core of our long-term competitive moat.

ROLE MISSION

We're looking for a builder to sit at the intersection of proprietary data, applied machine learning, and creative/social intelligence - building models and systems that turn one of the most unique datasets in the creator economy into insight and competitive advantage. This is hands-on and high-ownership: you'll work closely with engineering and product to translate data into decision-making tools, intelligence products, and AI-powered capabilities.

KEY OUTCOMES

  • Design, build, and deploy ML models and AI systems powering creator intelligence, audience analytics, and content performance products.
  • Take proprietary audience and creator models from feature engineering and training through to production deployment and monitoring.
  • Apply statistical rigour to extract actionable insight from large, complex, often unstructured datasets.
  • Work hands-on with LLMs and foundation models - fine-tuning, prompt engineering, RAG, and other post-training techniques.
  • Partner with business leaders to ensure statistical rigour underpins reporting and decision-support tools.
  • Contribute to the team's intellectual culture via technical blogs, internal research, and conference talks.

CORE COMPETENCIES

  • Building and shipping ML/statistical models in production - not just notebooks.
  • Strong Python fluency across the modern data science stack (PyTorch, TensorFlow, scikit-learn, or equivalent).
  • Operating at scale: large datasets, complex pipelines, and the engineering challenges that come with them.
  • Working with LLMs/foundation models and applying frontier ML research to real business problems.

YOU'LL THRIVE HERE IF

  • You approach problems from first principles and interrogate whether a model is the right tool before reaching for one.
  • You're intellectually rigorous and honest - careful experiment design, appropriate scepticism, clear communication of uncertainty.
  • You think of data as a strategic asset and connect technical work to the business questions it answers.
  • You're energised by hard, ambiguous problems in messy, real-world environments - you don't need a clean brief to do great work.
  • You're a builder first: you get models into production, not just into a deck.
  • You're high ownership, low ego, and commercially minded.
  • You're intellectually curious - you read research, build outside of work, and bring fresh thinking to the team.

IDEAL BACKGROUND

  • Demonstrable experience building and deploying ML or statistical models in production.
  • Strong Python and relevant DS library experience.
  • Background in consumer/enterprise data products, creator economy, or media analytics is a strong advantage.
  • Bonus: CS/ML research background, agentic AI or multi-model architecture experience, creator/audience/community data exposure, published research or open-source contributions, or time at organisations at the frontier of applied AI.
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