Top Senior Analysis Reporting Jobs in Rochester, NY

As a Data Engineer, you will develop solutions for customer-centric technology, ensuring platform integration and managing data architecture. Responsibilities include building data processes, maintaining data integrity, and collaborating cross-functionally to meet business challenges.

As a Senior Analytics Engineer, you'll build data pipelines and dashboards, partner with stakeholders for KPI development, and ensure data quality across the company.

Analyze large complex datasets to identify trends and anomalies, produce actionable insights and financial models, document processes, present findings to stakeholders, manage projects and client relationships, mentor junior staff, and support planning and delivery.

The Senior Clinical Research Associate manages site monitoring and relationships for clinical trials, ensuring compliance and patient safety according to GCP and regulations.

As a Senior Machine Learning Engineer, you'll build and deploy ML models for risk and fraud detection, leading technical efforts and collaborating cross-functionally.

Lead market and client-level fundraising data analysis and publish original research and benchmarks. Partner with Sales, Customer Success, and Marketing to produce ROI cases, client insights, and thought leadership. Present findings publicly at conferences, build repeatable insight frameworks and tools, and translate data into persuasive narratives for advancement leaders.

The role involves acting as a subject matter expert in Data and AI, providing technical expertise during sales processes for Azure-based solutions, and mentoring team members to enhance client experiences.

The Business Intelligence Senior Consultant develops BI strategies, implements solutions using Ellucian tools, and supports higher education clients with technical and functional consulting.

The Director of Data Analytics & Business Intelligence leads analytics functions, building models and dashboards while guiding a team. Responsibilities include analytics infrastructure management, cross-functional collaboration, and driving AI/ML initiatives.

Lead legacy-to-SaaS data migrations: design and execute ETL, extract/transform/load data, validate integrity, map business workflows to target models, engage clients, document processes, support governance, and train stakeholders to ensure accurate, secure conversions.