Top Senior Analysis Reporting Jobs in Hartford, CT

As a Senior Machine Learning Engineer, you'll build and deploy ML models for risk and fraud detection, leading technical efforts and collaborating cross-functionally.

The Staff Data Scientist will oversee Foodsmart's member growth analytics, focusing on marketing and product funnel optimization, experimentation, attribution modeling, and enhancing self-service analytic tools while collaborating closely with leadership and cross-functional teams.

The Senior Statistical Programmer will program and validate datasets for clinical trials, oversee deliverables, manage projects, and ensure compliance with industry standards. Requires strong skills in SAS and R for statistical programming.

As a Data Engineer, you will develop solutions for customer-centric technology, ensuring platform integration and managing data architecture. Responsibilities include building data processes, maintaining data integrity, and collaborating cross-functionally to meet business challenges.

The Senior Director will manage data partnerships and relationships to enhance Experian's Financial Services business, ensuring compliance and optimizing data ROI.

The Business Intelligence Analyst will analyze pharmaceutical transaction data, develop visual data models, and collaborate cross-functionally to drive insights and improvements in business strategies.

As a Senior Analytics Engineer, you'll build data pipelines and dashboards, partner with stakeholders for KPI development, and ensure data quality across the company.

The role involves acting as a subject matter expert in Data and AI, providing technical expertise during sales processes for Azure-based solutions, and mentoring team members to enhance client experiences.

The Director of Data Analytics & Business Intelligence leads analytics functions, building models and dashboards while guiding a team. Responsibilities include analytics infrastructure management, cross-functional collaboration, and driving AI/ML initiatives.

Lead legacy-to-SaaS data migrations: design and execute ETL, extract/transform/load data, validate integrity, map business workflows to target models, engage clients, document processes, support governance, and train stakeholders to ensure accurate, secure conversions.