Data Scientist - Remote

Company : Experis

Location : San Francisco, CA

Posted Date : 17 October 2025

Job Type : Other

Category : Mathematics

Occupation : Data Scientist

Job Details

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.