Job Details

Overview

Data Scientist

Were hiring a Data Scientist to turn data into decisions and ML products that drive impact. Youll own problem framing, EDA, feature engineering, model development / validation, experimentation, and clear storytellingpartnering with product and engineering to ship measurable outcomes.

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 Qualifications

• 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.