Top Senior Level Data & Analytics Jobs in Rochester, NY

As a Big Data DevOps Lead, you will improve efficiency in Big Data infrastructure, coordinate initiatives across teams, lead architecture design efforts, ensure system reliability, and support operational tools while also providing on-call support.

The Senior Data Analyst will work within the Analytics team to analyze seller behaviors, define key metrics, and drive decisions that improve the Supply product's effectiveness. Responsibilities include conducting analyses, performing A/B testing, partnering with engineers, and communicating insights to influence product development.

As a Data Engineering and Analytics Manager at Spark, you'll lead the data team, overseeing data engineering, analytics, and infrastructure projects. Your role involves managing and mentoring team members, building scalable data solutions in GCP, transforming messy data into structured formats, and creating dashboards for data-driven decision-making.

As a Principal Data Engineer, you will drive the direction of the Data Warehouse, design and optimize ingestion pipelines, and mentor team members. You will ensure data accuracy, monitor pipelines, comply with regulatory requirements, and collaborate with internal teams for comprehensive data integration.

As a Senior Data Scientist, you will leverage organizational data for insights that enhance user experiences and boost business efficiency. Key responsibilities include developing predictive models, deploying advanced analytics solutions, and collaborating with cross-functional teams to solve complex transportation challenges. The role emphasizes creativity, problem-solving, and a deep understanding of business needs.

The Staff Media Revenue Growth Analyst will perform data analyses and provide actionable insights to support advertising revenue growth. This role involves leading strategic initiatives, managing stakeholder relationships, and influencing decision-making to enhance product value and communication with advertising partners.

Develop and deploy advanced data science models using LLMs, GPT, and RAG. Utilize deep learning techniques to drive business growth and enhance functionality on the platform. Communicate findings to stakeholders.