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Data Scientist - Remote

Data Scientist - Remote

ExperisSan Francisco, CA, United States
23 hours ago
Job type
  • Full-time
  • Remote
Job description

Data Scientist

We're hiring a Data Scientist to turn data into decisions and ML products that drive impact. You'll own problem framing, EDA, feature engineering, model development / validation, experimentation, and clear storytelling-partnering with product and engineering to ship measurable outcomes.

Key Responsibilities

  • Translate business needs into data / science problems with clear success metrics.
  • Explore, clean, and join complex datasets; engineer high-signal features.
  • Build, validate, and iterate predictive / classification / ranking / NLP / time-series models.
  • Design and analyze experiments (A / B, multi-arm) and causal studies for trustworthy inference.
  • Communicate insights via narratives, visuals, and actionable recommendations.
  • Partner with product / engineering to productionize models and monitor performance.

Required Skills and Experience

  • 6-8+ years of applied data science experience in production or equivalent.
  • Strong foundations in statistics, probability, and experimental design.
  • Advanced SQL and proficiency in at least one general-purpose programming language, with hands-on experience using ML libraries and tooling.
  • Experience working with large datasets and familiarity with distributed data processing frameworks.
  • Proficiency in model evaluation, validation, and monitoring (offline / online metrics).
  • Fluency in data visualization and executive-ready communication.
  • Familiarity with MLOps practices and collaboration with data / platform engineering.
  • BS / MS in a quantitative field (or equivalent experience) and strong communication skills.
  • Preferred Qualification

  • Experience in specialized areas like NLP, forecasting, recommendations, or anomaly detection.
  • Knowledge of causal inference and A / B testing methods.
  • Hands-on work with feature stores, real-time data, or online ML systems.
  • Familiarity with cloud data platforms and modern warehouses.
  • Experience mentoring peers and contributing to cross-team projects.
  • Extra plus : publications, open-source contributions, or conference talks.
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