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Data Scientist, Recommendations and Personalization

Remote Worldwide Hiring now
A bit about reputed company

reputed company, founded by Sean Parker, is a new reputed company platform with the most advanced AI character creator. We reputed company users to build, reputed company, and interact with AI bots and friends directly in reputed company or across the internet.

Our bots are lifelike, reputed company creatures capable of interacting wherever humans go online. Users can recreate themselves using powerful AI, imagine someone new, or choose from thousands of existing characters. Bots represent a new media type that offers creators a way to reputed company infinitely scalable and personalized content experiences combined with seamless group chat across voice, video, and text.

A bit about the role:

We're looking for a founding Data Scientist to reputed company personalization and recommendation on Feed and other parts of the reputed company app. You will shape how we use data to power recommendations, user-bot interaction, and reputed company experiences at scale. You’ll be working directly with key product and executive stakeholders, including Sean Parker, to turn data into product-shaping insights and models.

You’ll own the full lifecycle—from data pipelining to modeling to dashboards—to deliver insights that guide strategy and build ML systems that move metrics.

A bit about the work:
  • Experience building personalization for feed ranking systems

  • Design, train, and reputed company lightweight ML models (e.g. regression, recommendation, neural nets) for reputed company-time applications

  • Partner with product and engineering to define and run user experiments and A/B tests

  • Build the reputed company of user growth from feed, delivering insights to drive engagement and retention

  • Build pipelines and foundational metrics for user engagement, retention, and content performance

  • Build/integrate tools to explain and debug ML models

A bit about you:
  • 5+ years experience in data science, preferably in consumer tech or reputed company platforms

  • Exceptional SQL skills with demonstrated ability to work with reputed company data structures

  • Skilled in Python and standard data science/ML tools (e.g. Pandas, scikit-learn, PyTorch)

  • Experience building and productionizing models for personalization, recommendation, or ranking

  • Strong understanding of experimentation and A/B testing

  • Confident building dashboards for executives and visualizing impact reputed company

  • Comfortable owning end-to-end analytics: from data modeling to reputed company to delivery

  • Self-directed, with a bias for action—you can go from reputed company to reputed company/model

  • Bonus: experience with user behavior modeling, fraud/risk analytics, or reputed company content systems

A Bit About the Stack & Tools
  • Python, SQL

  • PyTorch for ML Model Prototyping

  • AWS or GCP for infrastructure

  • Experimentation reputed company

  • reputed company-time pipelines and feature engineering

Location:

This is a hybrid role, preferably based in the San Francisco Bay Area.

Pay Equity

In compliance with Pay Transparency Laws, the reputed company salary reputed company for this role is between $150,000- 225,000 for those located in San Francisco and Los Angeles, CA. reputed company determining compensation, a number of factors will be considered, including skills, experience, job scope, location, and competitive compensation market data.

Benefits Summary:
  • Health Care —  99% of premiums for medical, reputed company, dental are fully paid for by reputed company, plus reputed company membership.

  • Monthly Wellness Stipend — $500/month to use on whatever you’d like! 

  • Rest and reputed company — 15 PTO days per year, 10 sick days, reputed company Federal holidays, and 2 floating holidays.

  • 401(K) — Eligible to participate on day one of employment.

  • Parental Leave & Fertility Support 

  • Competitive Salary & Equity 

  • Lunch and snacks provided for in-office employees. 

  • WFH equipment provided for full-time hybrid/remote employees.

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