Top Analytics Jobs in Hartford, CT

Leads data strategy for MetLife’s Group Benefits business by connecting business and Data & Analytics teams, establishing shared definitions, resolving ownership gaps, and improving governance and quality. The role leads Data Councils, supports Agile Release Trains, removes data-related blockers, and strengthens data foundations for decision-making, service delivery, analytics, and AI initiatives.

Own Eve’s go-to-market data models and semantic layer for governed metrics including pipeline, conversion, CAC, win rate, ARR, and bookings. Establish certification frameworks, modeling standards, documentation, alerting, and analytical application patterns across the organization. Partner with Sales, Marketing, Customer Success, and RevOps stakeholders, resolve conflicting metric definitions, enable AI-grounded data tools, review contributions, and mentor analytics engineers.

Analyze and optimize drug pricing using data-driven models, dashboards, reports, and strategic frameworks. Partner with Sales, Operations, Marketing, Finance, Product, pharmacy partners, and data teams to identify opportunities, define success metrics, improve reporting, and balance pharmacy economics with patient affordability. Serve as a trusted analytical advisor and support backend data development and query optimization.

Supports cross-channel marketing attribution and influence modeling by documenting data sources, defining business rules, mapping and normalizing interaction data, testing reporting prototypes, and recommending implementation steps. The intern also assists with AWS marketing data organization, segmentation research, data hygiene, process documentation, and stakeholder communications. The role requires analytical thinking, thorough documentation, clear communication, and collaboration across marketing and technical teams.

Leads enterprise data governance strategy, transformation, operating model modernization, accountability, and executive engagement. Partners with senior stakeholders to improve data trust, accessibility, regulatory alignment, risk management, analytics, AI readiness, and business outcomes. Represents the Data Office in strategic and regulatory forums, establishes roadmaps and performance measures, resolves cross-functional data challenges, and drives organizational change without direct authority. The role focuses on governance and transformation rather than engineering, coding, analytics delivery, or technical administration.

Leads a client-facing healthcare analytics team that designs and maintains prior authorization decision automation programs. Consults PaaS clients, develops strategic roadmaps, translates requirements into technical blueprints, analyzes authorization and claims data, and builds KPI reports using visualization tools. Manages direct reports, improves analytics processes and AI tooling, partners with product and engineering teams, and ensures automation outcomes and client KPIs are achieved.

Own Hometap’s product and marketing event-data ecosystem, including taxonomy, tracking plans, governance, Segment Protocols, schema validation, and source management. Partner with marketing, product, and engineering to define instrumentation and event specifications. Build monitoring for schema conformance, event volume, and property completeness, while documenting standards and managing event review and deprecation processes.

Supports data and analytics projects by designing ETL processes, developing data pipelines, integrating and validating data, and improving data quality. Creates Power BI reports and dashboards, troubleshoots data and storage issues, and helps enhance data warehouse and analytics solutions. The intern also explores AI-enabled tools, cloud platforms, and modern data engineering practices while collaborating with business partners.

Partners with HR leaders to translate business needs into scalable reporting and analytics solutions. Builds Workday reports, dashboards, self-service experiences, and Tableau visualizations; improves data quality, governance, automation, and reporting adoption. Applies product-oriented and Agile approaches to prioritize roadmaps, clarify decisions, and deliver incremental value. Explores responsible AI and Microsoft Copilot use while communicating effectively with senior stakeholders and handling sensitive HR data responsibly.

Leads an eight-person analytics engineering team and sets strategy for trusted semantic models, governed data, enterprise BI, AI-powered data access, and production data applications. Oversees data modeling, evaluation datasets, telemetry, LLM routing, governance, security, and self-service capabilities. Partners cross-functionally to establish engineering standards, roadmaps, and measurable business impact while hiring, coaching, and developing team members.

The Operations Data Analytics Manager will support strategic operations and supply chain initiatives by solving problems, analyzing data, and collaborating across teams to provide insights for decision-making and project alignment.

Build Deepgram’s governed decision layer above warehouse gold tables. Responsibilities include modeling cross-system entities, owning semantic and metrics definitions, creating agent-facing data tools and MCP surfaces, implementing data quality assertions and reconciliation checks, evaluating AI agent accuracy, and answering business questions while leaving reusable models behind. The role requires production-grade SQL and Python, semantic-layer ownership, strong data modeling judgment, AI-native workflows, clear writing, and comfort building infrastructure from scratch.

Lead and scale Ticketmaster’s product experimentation program by establishing governance, standards, onboarding, and measurement practices. Configure and monitor Optimizely experiments, design statistically rigorous A/B and multivariate tests, analyze results, and translate findings into product recommendations. Define digital metrics, identify fan-experience opportunities, build self-service analytics resources, and partner with Product, Design, Engineering, Research, and Analytics teams to support data-informed decisions.

Analyze personal loan product performance, customer behavior, funnel conversion, campaigns, and key performance metrics. Design measurement frameworks, identify tracking gaps, conduct root cause analysis, develop A/B tests, support analytics infrastructure, and create dashboards. Partner with Product, Engineering, Data Science, and Business teams to translate insights into product improvements and increased origination volume.

Leads the enterprise business intelligence and analytics strategy, manages BI and data analysts, and oversees analytics roadmaps, projects, platforms, dashboards, and vendor relationships. Translates complex data into actionable financial and business insights, supports SAP and Power BI platform upgrades, manages delivery timelines and resources, and coaches team members. The role also drives stakeholder engagement, continuous improvement, talent development, and data-driven decision-making across the organization.

Owns performance analytics for General Liability claims processes, monitoring trends, diagnosing root causes, evaluating process improvements, and recommending priorities to leadership. Partners cross-functionally with claims, actuarial, underwriting, data, and field operations teams. Presents metrics and action items, validates deployed solutions, supports process optimization, and translates customer and business needs into actionable data-driven solutions.

Own Step’s analytics data models, transformation pipelines, metric definitions, semantic layer, and data quality practices. Partner with Product, Marketing, Engineering, Risk, Growth, and Finance to establish trustworthy data foundations and enable self-service analysis. Build reusable query, visualization, and code components; apply AI-augmented workflows; and collaborate with data scientists, analysts, and platform engineers. The role requires strong SQL, modeling, pipeline, BI, communication, and independent ownership skills, with occasional travel for team onsites.

Build and maintain scalable data transformation pipelines, analytics-ready datasets, data warehouses, data marts, and reusable data models using SQL and dbt. Implement data quality testing, validation, monitoring, documentation, and governance while optimizing warehouse performance and integrating multiple data sources. Partner with analysts, product managers, and business stakeholders to support dashboards, KPI reporting, business intelligence, and strategic analytics initiatives.

Owns a six-month analytics engineering engagement covering scalable Snowflake architecture, marketing and sales ingestion, finance automation with LLM agents, data reconciliation, and governed Tableau reporting. Builds production-ready pipelines, data models, quality monitoring, human-in-the-loop controls, and row- and column-level security. Delivers documentation and knowledge transfer while coordinating independently with finance and publishing stakeholders.

Maintains and monitors Azure Databricks data pipelines, troubleshoots data issues, collaborates with stakeholders on data requirements, documents processes, performs backups and disaster recovery drills, and supports data access and usage. The role requires extensive data engineering experience, Azure expertise, incident management knowledge, and strong problem-solving skills.

Provides technical leadership for enterprise analytics by architecting SQL-based transformations, scalable data models, semantic layers, and governed datasets. Builds analytics products supporting healthcare KPIs, patient journeys, scheduling, retention, and operational decisions. Establishes analytics engineering standards, testing, documentation, lineage, and code-review practices; troubleshoots data-quality issues; partners with business and technical stakeholders; and mentors analysts in SQL, dimensional modeling, dbt, and governed data-product development.

Supports analytics product improvements by researching data issues, designing reports, documenting business requirements, developing use cases, and conducting user acceptance testing. The role creates training materials, facilitates user training, supports credit unions and internal users, promotes business intelligence practices, and helps transition analytics solutions into business operations.

Leads marketing and enrollment analytics across acquisition and conversion funnels. Analyzes channel performance, ROI, attribution, forecasting, experimentation, and marketing mix modeling; develops recommendations for budget allocation and performance improvement. Uses Power BI, SQL, Python or R, and institutional and marketing datasets to build models, automate monitoring, identify anomalies, and support cross-functional decisions. Owns marketing measurement standards, data quality, tracking, and analytical roadmap while partnering with Marketing, Enrollment, Field, and Institutional Analytics teams.

Leads CookUnity’s Advanced Analytics function, setting strategy and partnering with Product, Finance, Operations, Marketing, and leadership. The role involves experimentation, causal inference, retention and growth analysis, marketing measurement, product impact evaluation, and translating insights into business decisions. This hands-on player-coach will guide complex analytical work, develop analysts, improve analytical rigor, and shape team structure and priorities.

Supports Somali-speaking learners in a fully virtual data analytics program. Responsibilities include answering questions, facilitating breakout rooms, holding office hours, reviewing materials, grading assignments, providing feedback, recording walkthroughs, monitoring learner progress, and escalating concerns. The role also requires supporting live sessions, communicating in Somali and English, attending onboarding and staff meetings, and submitting weekly progress reports.