Top Remote Data & Analytics Jobs in Rochester, NY

Analyze, clean, transform, and integrate data from multiple sources; identify trends, anomalies, KPIs, and business insights; and create scalable Tableau dashboards, reports, and visualizations. Develop Tableau Prep workflows, support data governance, optimize data retrieval with engineering and IT teams, and communicate actionable recommendations to technical and executive stakeholders. The role also uses statistical analysis, ServiceNow operational analytics, and business intelligence tools.

Optimize and administer SQL Server databases supporting multi-terabyte healthcare claims data. Responsibilities include tuning T-SQL, execution plans, indexing, partitioning, statistics, tempdb, memory, backups, high availability, and database monitoring. The role develops stored procedures and data structures, identifies claims overpayments, automates data mining processes, investigates root causes, and mentors analysts. Collaboration with infrastructure and business teams is required, along with ownership of small projects and performance improvements.

Leads strategy, planning, and execution of customer EMR integrations for PhareOS. Oversees end-to-end data delivery, integration quality, process standardization, tooling, vendors, and platform enhancements. Builds and scales the data integration team, manages resources and senior client stakeholders, and drives innovation across integration methods and operating models. Requires extensive healthcare data integration leadership, HL7/FHIR and interface engine expertise, SQL proficiency, and strong program management skills.

Own experimentation analytics across Product and Marketing, including A/B and multivariate test design, causal inference, statistical analysis, dashboards, dbt models, and data infrastructure. Translate results into business recommendations, improve experimentation frameworks and self-service reporting, partner with engineering on instrumentation, mentor analysts, and manage the analytics roadmap.

Build and govern clinical analytics datasets, SQL transformations, data marts, dashboards, and reporting solutions for clinical quality, patient safety, outcomes, regulatory, and research initiatives. Partner with clinicians, executives, researchers, and enterprise data teams to define metrics, ensure data integrity, implement testing and governance frameworks, and deliver trusted executive, board, regulatory, and clinician-facing insights using modern cloud data platforms.

Leads analytics strategy and delivery by partnering with business stakeholders, customers, and data engineering teams. Defines and prioritizes analytical roadmaps and backlogs, translates business needs into technical requirements, supports data governance, coordinates development, communicates progress, and manages user acceptance testing. The role promotes data-driven decision-making and ensures analytical solutions deliver sustainable business value.

Design and modify data solutions using Databricks and Palantir Foundry; build data models and reports from ERP and legacy-system datasets; define and execute tests; and translate stakeholder reporting needs into technical specifications. The role requires SQL, Python, PySpark, database architecture, cloud architecture, software engineering practices, independent execution, documentation, and collaboration. It supports an Army client in a hybrid Arlington, Virginia environment and requires an active Secret clearance.

Leads the sales and partnerships insights function supporting sponsorship, ticketing, premium sales, and revenue decisions. Builds analytics standards, reporting, forecasting, pricing, pipeline, renewal, and performance measurement capabilities across decentralized properties. Recruits and manages an analytics team, partners with enterprise data and CRM teams, deploys models and AI-enabled tools, and advises executives, venue leaders, and clients on commercial strategy and outcomes.

Build governed, reusable Data 360 products and scalable transformation pipelines using SQL, Python, dbt, and Snowflake. Establish dimensional models, semantic layers, trusted metrics, data quality controls, lineage, and governance for clinical, laboratory, operational, and commercial data. Ensure PHI and genomic data compliance while integrating AI-native engineering practices. Collaborate with cross-functional stakeholders, lead architecture decisions, validate data products, resolve complex data issues, and mentor engineers.

Establishes data quality, freshness, coverage, and delivery baselines across multiple brands; connects data gaps to commercial impact; identifies automation opportunities; defines SLAs; documents data standards, source specifications, governance policies, and requirements; and delivers executive-ready insights. The role partners with Data Operations, Sales, Customer Success, Product, and Engineering to improve data quality, automate workflows, manage governance, and track business outcomes.