Senior Data Scientist

FlightStory

Media
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years of experience in data science or machine learning roles
  • Expertise in deploying ML/statistical models in production environments
  • Strong Python fluency, familiarity with PyTorch, TensorFlow, and scikit-learn
  • Background in handling large datasets and complex data pipelines
  • Experience in consumer/enterprise data products or media analytics is advantageous

Responsibilities

  • Design, build, and deploy machine learning models for creator intelligence and audience analytics
  • Transform audience and creator models through feature engineering to production
  • Extract actionable insights from large, complex datasets using statistical methods
  • Work directly with LLMs to fine-tune and apply post-training techniques
  • Collaborate with business leaders to ensure data-driven decision-making
  • Contribute to the team's knowledge-sharing through technical writing and talks

Benefits

  • Opportunity to work at the intersection of data and innovation
  • High ownership role with direct impact on decision-making tools
  • Collaborative environment with engineering and product teams
  • Culture that promotes intellectual curiosity and ongoing learning
  • Flexibility to tackle complex, real-world problems
Full Job Description
SENIOR DATA SCIENTIST

COMPANY: STEVEN.COM

REPORTING TO: HEAD OF DATA INTELLIGENCE

LOCATION: LOS ANGELES

SALARY: UP TO $185,000
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.


Department Steven.com Locations Los Angeles, US

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