Top Remote Analysis Reporting Jobs in Rochester, NY

Leads Ford’s multi-touch attribution team and enterprise marketing measurement capability. Responsibilities include managing eight employees, vendor relationships, data pipelines, analytics intake, taxonomy governance, data quality, statistical validation, causal inference, dashboards, and reporting. The role uses GCP, Python, and SQL to automate attribution workflows, evaluates marketing effectiveness, oversees budgets and contracts, partners with media agencies, and communicates insights to technical and business stakeholders. It also promotes AI/ML and generative AI adoption while ensuring privacy, policy compliance, and alignment with Marketing objectives.

Build and maintain a regulatory reporting data platform using SQL and dbt, including models, automated validations, data pipelines, and testing. Investigate data issues end to end, validate submissions, support audits and legal data requests, monitor upstream changes, collaborate with product, engineering, compliance, and leadership, and participate in on-call coverage. WOOF WOOF

Performs accurate data entry, verification, updating, cleanup, organization, and maintenance across databases, spreadsheets, and digital systems. Maintains electronic records, converts documents into digital formats, prepares basic reports, retrieves information, tracks assignments, and supports scanning and filing. The role requires confidentiality, attention to detail, strong organization, dependable independent work, effective time management, and reliable remote-work capabilities.

Performs advanced data extraction, statistical analysis, modeling, forecasting, and visualization using enterprise data sources. Builds and maintains Power BI dashboards and Snowflake data models, supports data governance and regulatory reporting, and translates business needs into actionable insights. Serves as a trusted analytics consultant, leads reporting and analysis projects, presents findings to technical and non-technical stakeholders, and improves reporting through automation and standardized methodologies.

Design, build, and operate production data pipelines using Python, Spark SQL, and Airflow. Canonicalize healthcare and customer data into trusted internal models, optimize distributed processing, enforce schemas, and implement quality checks and observability. Support customer onboarding, streaming pipelines, troubleshooting, on-call operations, and platform best practices while collaborating with product, analytics, engineering, data science, and customer teams.

Leads Point C’s enterprise analytics strategy, data platforms, governance, reporting, and insights delivery. Builds trusted analytics for brokers, employers, sales, operations, finance, and clinical teams; oversees data integration, quality, standardization, and acquisition-related analytics. Develops a scalable agile analytics organization and aligns roadmaps, metrics, and delivery standards with business growth and executive decision-making.

Administer and optimize production and non-production databases for a large-scale VA data migration. Responsibilities include installation, patching, performance tuning, backup and recovery, security, AWS database provisioning, data conversion, validation, troubleshooting, high availability, disaster recovery, and technical documentation. The role collaborates with developers and analysts across on-premises and AWS environments while ensuring database availability, integrity, and security.

Analyze marketing and media data to measure TV and streaming campaign effectiveness, validate data and assumptions, identify actionable insights, and create clear visualizations and client-ready presentations. The analyst will use Excel, BI and data platforms, SQL, and AI tools to accelerate analysis while independently validating results and explaining methodologies, KPIs, and recommendations to internal teams and clients.

Own data partner specification negotiations, data mapping, Ascend platform configuration, and internal QA across multiple implementations. Review file specifications, normalize schemas, validate test files, document data dictionaries, and route non-standard requests to Product or Customer Engineering. Coordinate with delivery and engagement teams on UAT, defects, readiness, and capacity constraints. Develop repeatable QA frameworks, implementation playbooks, procedures, and training materials while ensuring configurations meet quality standards before go-live.

Design, build, and own business-critical data infrastructure, including AWS Glue and Spark pipelines, cloud warehouse or lakehouse systems, orchestration, and Tableau BI platforms. Define event-driven contracts, data models, schemas, observability, and batch or streaming architectures across multi-tenant, multi-region environments. Collaborate across producer and consumer teams while owning production data infrastructure and outcomes end to end.