Top Remote Senior Level Data Science Jobs in Rochester, NY

As a Senior NLP Data Science Researcher, you'll utilize advanced AI techniques to work on novel healthcare projects, focusing on training NLP and LLM models, building Python-based inference pipelines, and conducting data analysis and model validation.

As a Senior Data Scientist at RevenueCat, you will create data models, dashboards, and reports to help developers make informed decisions. You'll collaborate with product and data teams to enhance data features, build predictive models, and contribute to the data tech stack, ultimately shipping features that drive customer value.

The Senior Data Scientist will develop machine learning models to enhance products and solutions at DICK’S Sporting Goods, conducting data-driven analyses, and providing actionable insights. Responsibilities include advanced analytics, data collection, and improving data strategies to boost business performance.

As a Senior Data Scientist, you will translate complex business questions into quantitative analysis, enable data-driven decisions, and develop visualizations. Responsibilities include aggregating data with SQL, supporting ETL processes, and building dashboards to inform product and operational teams. Strong analytical and communication skills are essential.

The Lead Data Scientist will build and mentor a team, define the technical vision, design advanced search algorithms, develop machine learning models to personalize user experiences, conduct data analysis, and collaborate with product teams to turn business needs into data projects.

As a Senior Data Scientist, you will collaborate with product teams to generate insights that enhance growth and engagement. Responsibilities include building dashboards, delivering analyses, designing experiments, and communicating findings to drive product improvements and customer experience.

As a Principal Data Scientist II (AI), you will shape AI strategies and develop innovative AI solutions. Responsibilities include defining AI architecture, collaborating with data scientists, integrating AI capabilities across the platform, providing technical leadership, and driving product innovation.