Experis
Overview
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. 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.
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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. 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.
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