Top Senior Level Data Science Jobs in Rochester, NY

The Manager of Marketing Data Science will spearhead initiatives in data utilization, predictive modeling, and machine learning to enhance marketing strategies and optimize performance for Dow Jones' Enterprise clients. This role involves collaborating with technology and marketing teams to establish robust data infrastructures and ensure data governance, ultimately driving actionable insights and improving customer retention.

The Principal Applied Scientist will lead the research and development of recommendation algorithms, focusing on model optimization and system scalability. They will mentor ML engineers, influence AI strategy, and collaborate with teams to enhance product innovation and customer experiences at Wizard.

The Senior Data Scientist at OneDigital is responsible for developing new models and tools for client projects related to health benefits strategies. They will work on data visualization, web application development, and providing R&D support for model enhancements. The role requires a Bachelor's/Master's degree in a relevant quantitative discipline and 4+ years of experience in data science or related fields.

Deliver scalable, performant ETL processes in multi-tenant cloud infrastructures, focusing on healthcare data. Design and implement enterprise data schemas, clean and transform data sets, and operate ETL software components. Collaborate with team members and clients to achieve scalability and high performance.

The Senior Computer Vision Scientist will develop predictive models using 3D data, utilizing machine learning and statistical modeling techniques. They will clean and prepare data for analysis, leverage cloud resources for data processing, and extract data from databases, while continuously iterating on solutions in a collaborative environment.

As a Staff Data Scientist, you will develop statistical and machine learning models to enhance the operations platform. Responsibilities include leveraging data to solve problems, collaborating across teams, implementing predictive models, and mentoring teammates. Excellent communication and technical skills are essential, along with a strong background in Python and statistical software.

Conduct high-level research on forest carbon dynamics, lead projects for enhancing carbon storage, analyze data using statistical and GIS tools, collaborate with stakeholders for conservation strategies, write grant proposals and reports, lead field teams in data collection, engage with carbon market stakeholders