Top Remote Data & Analytics Jobs in Rochester, NY

Lead development and execution of forward-looking drug spend forecasting models, quantify macro-market impacts, partner with clinical and pricing teams, translate analytical findings for executives and clients, build automated reporting with Data Analytics, support sales/proposals, engage brokers/consultants, and drive strategic growth projects.

The role involves leading comprehensive testing of Federal Amazon Connect solutions, ensuring compliance with security standards, mitigating risks, and collaborating with cross-functional teams to deliver high-quality products.

The Solutions Analyst delivers reporting and operational outputs, analyzes datasets, resolves issues, maintains solution components, and collaborates with teams to improve efficiency.

Build and maintain Sigma dashboards, analyze client workup data, develop predictive models to forecast case progression, evaluate team productivity, translate data into actionable insights, document methodologies, and collaborate with data engineering and legal teams to improve reporting and operations.

Analyze commercial data for sales, marketing, service and support to create metrics and insights for optimization. Collaborate with cross-functional teams to provide data-driven recommendations and manage business intelligence tools.

Build and maintain AWS-based ETL pipelines (Glue/PySpark, MWAA/Airflow, Lambda) to ingest and process terabytes of financial data into an S3 data lake using Iceberg/Parquet. Implement metadata, monitoring, tests (90% coverage), materialized views (Trino/Athena), CloudFormation deployments, documentation, and support agile delivery and operations for federal clients.

The Databricks Architect will design and implement scalable data and analytics platforms, optimize data pipelines, and mentor team members while ensuring alignment with business goals.

Perform customer analytics and lifecycle measurement for subscription and auto insurance products. Build dbt/Snowflake data models, Tableau dashboards, survival and churn analyses, propensity datasets, A/B tests, pricing and LTV analyses, and recommendation logic. Partner with data engineers, data scientists, product, and marketing to operationalize personalization and inform retention, pricing, and product strategies.

Manage and optimize the Business Intelligence engineering team, develop BI strategy, oversee project management, and ensure data accuracy.

Analyze historical demand, occupancy, transactions and competitor pricing to optimize daily, monthly, and event pricing. Build dashboards, deliver revenue insights to leadership, and collaborate with Operations and Marketing to implement pricing and promotional strategies while maintaining data integrity.