Top Data & Analytics Jobs in Providence, RI

Lead production of federal species range maps for marine and anadromous taxa. Aggregate, normalize, transform, and validate spatial data; analyze habitat intersects; coordinate iterative reviews with FWS and NOAA SMEs; prepare QA documentation; and secure government sign-off for map deliverables.

Design, build, deploy, and maintain AWS-based data and AI/ML infrastructure for enterprise agentic AI platforms. Develop data lake pipelines, observability systems, agent-enablement tooling, and production MLOps/LLMOps capabilities. Own features end-to-end, contribute to architecture and design decisions, optimize reliability, scalability, security, and cost, and collaborate with AWS Professional Services, client teams, and junior engineers.

Designs and maintains healthcare analytics infrastructure, production data models, semantic layers, and transformation pipelines using advanced SQL and analytics engineering practices. Integrates payer claims, EMR, clinical, attribution, quality, and operational data. Performs ad hoc analysis, defines standardized healthcare metrics, validates data quality, optimizes queries, documents data flows, and partners with clinical, operational, IT, and payer stakeholders to support value-based care and enterprise reporting.

Lead complex SQL-based analyses of customer, marketing, ROI, and business data. Translate findings into actionable recommendations, reports, presentations, customer QBRs, and strategic insights. Guide Business Data Analysts, establish analytical best practices, prioritize requests, automate reporting, and collaborate with Customer Success, Marketing, Product, and Operations teams.

Lead product experimentation and analytics across three product squads. Design experiments, define product metrics, analyze patient and clinician behavior, build dashboards, apply causal inference, and communicate actionable insights. Partner with product, engineering, design, clinical, operations, and data teams to improve instrumentation, data quality, and evidence-based healthcare product decisions.

Coordinates data and process activities for a Managed Services Center, including ServiceNow CMDB reconciliation, data entry and validation, contract updates, quality assurance, task tracking, documentation, auditing, and business continuity support. Collaborates with internal teams and vendors to maintain accurate records, resolve discrepancies, and support ServiceNow operations. The role is remote and highly keyboard-intensive.

Design, develop, and maintain Customer Data Platform solutions and data pipelines to create unified customer profiles, manage identity resolution, enable audience segmentation and activation, ensure data quality and governance, and support integrations with marketing, CRM, and cloud data systems.

Develop and administer Power BI reports, dashboards, data models, visualizations, and refresh schedules for a federal customer. Connect and transform data from varied sources, troubleshoot data and reporting issues, and translate complex information into actionable insights. Create requirements, designs, SOPs, training materials, and client documentation while collaborating with technical teams and stakeholders. The role requires a current Secret clearance, a bachelor’s degree or equivalent experience, and at least four years of Power BI and big data/cloud experience.

Analyze qualitative and quantitative customer feedback, behavioral data, and operational metrics to identify user pain points and root causes. Develop dashboards, KPIs, reporting, and measurement frameworks; quantify experience impacts; and provide evidence-based recommendations. Partner cross-functionally with Product, Engineering, Marketing, Data, and Support leaders to influence prioritization, evaluate initiatives, and improve customer satisfaction, usability, loyalty, adoption, and support demand.

Leads enterprise data architecture for Customer 360, CDP, identity resolution, marketing, personalization, real-time activation, paid media, measurement, and AI capabilities. Designs unified data models, streaming and batch integrations, governed activation patterns, data contracts, APIs, observability, and security controls. Partners with business and technical leaders on roadmaps, architecture reviews, vendor evaluations, and implementation decisions while mentoring engineering teams and ensuring privacy, compliance, and responsible AI standards.