Top Remote Data & Analytics Jobs in Hartford, CT

Analyze market and live data to set dynamic ticket prices using Uptick, build strategic pricing recommendations, communicate with clients about strategy and performance, and collaborate with BI and engineering to improve product performance.

Analyze healthcare operations data to identify bottlenecks, model advocate capacity and supply-demand, build scalable Hex dashboards, refine SQL and dbt data transformations, and translate complex findings into operational recommendations. The role partners with Operations, Engineering, Product, Marketing, and Finance to improve workflows, reporting, resource allocation, and business outcomes across the patient and advocate journey.

Leads LTK’s Data Engineering team, owning technical direction, architecture, pipelines, data products, governance, quality, reliability, and platform modernization. Manages and develops engineers, drives roadmaps and complex initiatives, partners with cross-functional stakeholders, and balances scalability, security, performance, cost, and business priorities. Establishes engineering standards, improves operational practices, manages risks and dependencies, and builds trusted, reusable data capabilities supporting analytics, reporting, products, and AI use cases.

Support Items Master Data Management by collecting, cleansing, and analyzing supply chain product, contract, and pricing data. Build SQL-based reports and dashboards, ensure data quality and governance, support system implementations and migrations, and collaborate cross-functionally to drive standardization and operational improvements.

Supports information collection and organization for manuals, training materials, installation guides, proposals, and reports. Edits technical and customer-facing documentation, assists with financial and administrative tasks, and maintains systems, operations, and procedural documentation libraries. Collaborates remotely with project managers, requirements analysts, Scrum Masters, developers, testers, and government stakeholders in Agile ceremonies while complying with CUI and cybersecurity requirements.

Manage Epic Cogito reporting projects for healthcare organizations by gathering requirements, designing and developing reports, performing testing and validation, and providing post-implementation support. Collaborate with internal and external stakeholders, solve complex problems, and manage multiple projects independently while delivering healthcare IT and analytics solutions.

The Director of Biostatistics leads statistical strategy and analysis for clinical trials in oncology, collaborating with clinical teams and regulatory bodies.

Supports the Product Innovation Team by modifying and optimizing SQL queries, visualizing data with BI tools, identifying insights, and analyzing enhancements. Participates in coding, testing, documentation, and discussions while providing customer service and managing multiple tasks. The internship requires at least 30 hours per week and emphasizes advanced Excel and visualization skills, plus familiarity with Python and SQL.

Build and maintain FinOps data pipelines, BigQuery and dbt models, cost attribution systems, forecasting and anomaly detection models, and cost-versus-revenue analytics. Identify and implement AWS and GCP savings opportunities, automate governance with Python, Terraform, and Lambda, and partner with Engineering, Finance, Product, and leadership on cloud costs, forecasting, reporting, and architecture decisions.

Designs, builds, and maintains scalable ETL and data processing pipelines supporting analytics, forecasting, risk, and customer insights. Leads complex SQL development, data modeling, governance, quality, lineage, security, and compliance. Partners with engineering, finance, sales, compliance, product, analysts, and data scientists to translate requirements into reliable workflows. Evaluates emerging technologies, leads proof-of-concepts, and develops automated solutions using Python, Spark, Databricks, cloud platforms, orchestration tools, and modern data warehouses.