Top Remote Analysis Reporting Jobs in Hartford, CT

As a Staff Analytics Engineer, you will bridge data engineering, data science, and business analytics to generate actionable insights, build data models, and empower stakeholders across the organization.

Lead end-to-end data science initiatives: design, deploy, and monitor production ML models for credit risk, pricing, collections, and fraud. Partner cross-functionally to integrate models, set development standards, mentor team members, and maintain reliable, scalable machine learning pipelines and monitoring systems.

Lead analytics for marketing and customer acquisition: build dashboards, design and evaluate A/B tests, monitor conversion funnels, develop multi-touch attribution reporting, migrate reports to new systems, combine structured and unstructured data, and partner across Marketing, Sales, Finance, Operations, Credit, and Technology to turn insights into automated actions.

The Senior Portfolio Lead will oversee data management services for clients, ensuring quality deliverables, strategic oversight, and optimal clinical data flows, while leading cross-functional teams and managing complex client relationships.

Lead design and implementation of a unified event-tracking data platform. Collaborate with Data, Product, and Engineering to build reusable event-publishing frameworks, monitoring/alerting, and deprecate legacy systems. Coach mid-level engineers, influence roadmap and processes, manage cloud/SaaS spend, create documentation, and participate in on-call rotations to ensure platform reliability and data trustworthiness.

The Senior Performance Strategist manages key client relationships, optimizes performance, drives projects, supports troubleshooting, and mentors junior members to enhance campaign strategies and processes.

The Senior Data Engineer will architect, build, and maintain scalable data pipelines and infrastructure, mentor junior engineers, and collaborate on data solutions for Openly's insurance platform.

The Senior Data Engineer will own and evolve data pipelines, collaborate with teams for data models and pipelines, optimize ETL processes, and implement data storage solutions.

The role involves assessing fraud program effectiveness, compliance with regulations, and providing strategic insights for risk management within the financial services industry.

Lead design and implementation of scalable, HIPAA-compliant data pipelines and platforms for healthcare ML. Build ETL, orchestration, and tooling for processing EHR, claims, pharmacy, and bioinformatics data; collaborate with data scientists to produce modeling-ready datasets and ensure data quality, reliability, and operational excellence.