Diverse Lynx
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. Diverse Lynx LLC is an Equal Employment Opportunity employer. All qualified applicants will receive due consideration for employment without any discrimination. All applicants will be evaluated solely on the basis of their ability, competence and their proven capability to perform the functions outlined in the corresponding role. We promote and support a diverse workforce across all levels in the company.
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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. Diverse Lynx LLC is an Equal Employment Opportunity employer. All qualified applicants will receive due consideration for employment without any discrimination. All applicants will be evaluated solely on the basis of their ability, competence and their proven capability to perform the functions outlined in the corresponding role. We promote and support a diverse workforce across all levels in the company.
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