Top Remote Senior Level Data Science Jobs in Rochester, NY

As a Staff Data Scientist at Enigma, you will leverage machine learning and statistical methods to enhance data accuracy and usability. You will work within cross-functional teams, develop innovative solutions, validate results against real-world data, and contribute to critical product developments that impact small businesses' access to financial services.

The Senior Revenue Operations Analyst will lead analytics projects that inform decision-making across Go-To-Market functions. Responsibilities include coordinating cross-department initiatives, improving analytics processes, ensuring data integrity, and conducting analyses to support revenue operations.

The Senior Data Scientist will analyze resident health and care data to provide insights and feedback, design and maintain algorithms, integrate new datasets, create visualizations, and collaborate with various teams to address business needs using data.

As a Sr. Data Scientist, you will lead the development of advanced scoring and indexing models for predicting business outcomes, collaborate with teams to integrate solutions, conduct data analysis, and ensure the accuracy of models while communicating insights to stakeholders.

As a Senior Data Scientist at Entefy, you will influence the future of productivity through advanced analytics. Responsibilities include delivering insights from structured and unstructured datasets, leading other data scientists, and employing strong data visualization skills.

The SVP will lead the Data, AI, and Automation organization, driving a strategic transformation across global operations. They will develop and implement a comprehensive AI and data strategy, collaborate with cross-functional teams to integrate solutions, and ensure performance measures align with business outcomes, emphasizing digital innovation and talent development.

Responsible for developing tailored data science solutions, leveraging machine learning techniques to transform complex datasets into actionable insights, communicating findings, designing scalable models, and working cross-functionally with teams to integrate data science solutions.