Top Analysis Reporting Jobs in Buffalo, NY

Design, build, and maintain scalable ETL/ELT data pipelines on Databricks and AWS S3; manage large geospatial and temporal datasets; productionize ML models; implement data validation, testing, and monitoring; optimize storage and processing; document workflows; collaborate cross-functionally.

The DMS Data Engineer is responsible for analyzing raw data, building data systems and pipelines, conducting complex data analyses, and collaborating on projects to enhance data quality and reliability.

Lead analytics for Omnichannel retail/restaurant/CPG partners: act as primary analytics contact for Sales, manage analytic engagements and team capacity, perform SQL-based analysis, craft data-driven narratives and recommendations, influence campaign strategy, represent analytics in cross-functional settings, and automate insights using AI-enabled tools.

The Senior BI Analyst will gather requirements, develop scalable reporting solutions, and create dashboards using Power BI, ensuring data-driven decisions across the organization.

Lead design and delivery of Workday reporting and analytics for AMS clients: build advanced/matrix/trending/composite reports, dashboards, Discovery Boards, Worksheets, and complex calculated fields; gather requirements, optimize reports, mentor junior consultants, and provide Workday best-practice guidance.

Trace3 seeks enthusiastic individuals for its Data Intelligence Team. The role focuses on innovative technology solutions and consulting services, fostering a collaborative and dynamic work environment.

Perform data extraction from SQL/NoSQL systems, validate and transform data, and run statistical and psychometric analyses (IRT, reliability, norming). Validate assessment logic, define quality metrics, design research and simulation studies, and present findings via reports and dashboards. Collaborate cross-functionally and maintain current psychometric and data engineering practices.

The Data Scientist designs and builds data structures for AI applications, manages vector and feature stores, leads data discovery, and collaborates on responsible data use while ensuring high-quality, governed datasets for ML models and applications.

The role involves leading global forecasting and performance management, setting standards, overseeing processes, collaborating with cross-functional teams, and developing a high-performing team in the oncology biotech sector.

Perform part-time quality audits and evaluations of task outputs, define and refine quality benchmarks and scoring rubrics, analyze audit results to produce actionable insights and reports, and recommend process improvements to raise output quality.