Data Scientist

• Lead the strategy, development roadmap, and lifecycle of data products and platforms
• Define the roadmap for data solutions
• Collaborate with cross-functional teams
• Ensure data products are scalable, reliable, and user-friendly
• Monitor and improve data quality, reliability, and user adoption of data tools
• Define and track success metrics for data products

Staff Data Product Manager

• Manages a small team of data scientists and data engineers to research, design, develop, deploy, and maintain machine learning, AI, and agentic AI solutions supporting the Claims organization.
• Communicates project progress, insights, results, and recommendations to business partners and senior leadership.
• Manages project scope, expectations, and timelines.
• Collaborates with Data Engineering, IT, and business partners to operationalize machine learning and AI solutions.
• Follows the model governance process including planning, documentation, validation, deployment, monitoring, and review.
• Oversees model performance and supports ongoing monitoring and continuous improvement of deployed solutions.
• Develops and mentors team members to maintain technical excellence in AI/ML, software engineering, and solution design.

Data Science Manager

• Responsible for mining big data, interpreting and analyzing complex data sets
• Develops and deploys predictive models to analyze company performance and improve customer experiences
• Applies statistical techniques and machine learning algorithms to identify trends within Mazda data
• Collaborates closely with data engineers, analysts, and business stakeholders to integrate data-driven solutions

• Lead the enterprise IT Data Governance and Information Management Program for unstructured data, including program strategy, roadmap development, milestones, dependencies, and measurable outcomes.
• Establish and maintain the governance model, roles, responsibilities, decision forums, and escalation paths needed to support enterprise information management practices.
• Drive adoption of standards for document and information handling, including record identification, retention requirements, sensitivity labeling, document purpose, sharing permissions, download/copy restrictions, and lifecycle management.
• Partner with business unit leaders and designated data owners to assess current-state practices, identify gaps, define remediation plans, and track business progress toward compliance and housekeeping objectives.
• Lead senior-level status meetings and steering updates; present program health, risks, dependencies, progress metrics, business unit performance, and required decisions in a concise and actionable manner.
• Coordinate with Legal, Compliance, Cybersecurity, Privacy, and Internal Audit to ensure the program supports regulatory obligations, defensible discovery, data minimization, and incident readiness.
• Oversee development of repeatable processes and playbooks for data discovery, audit response, cyber response support, tabletop exercises, and preparedness simulations.
• Drive cross-functional planning for data protection capabilities supported by Microsoft Purview and related platforms, ensuring alignment between business requirements and technical control implementation.
• Define and monitor KPIs, dashboards, scorecards, and maturity measures to track adoption, remediation progress, policy adherence, and control effectiveness.
• Build strong working relationships across IT and the business; influence stakeholders to take action, resolve barriers, and improve long-term information management discipline.
• Ensure appropriate documentation of decisions, risks, approvals, standards, and process changes using structured governance and reporting practices consistent with enterprise program management expectations.

Program Manager, Data and Information Governance

• Design, develop, and deploy NLP and LLM-powered models that extract meaning, intent, outcomes, and sentiment from call, chat, and other digital interactions.
• Help translate complex data into actionable insights, ensuring AI-driven solutions are not only built, but adopted and impactful.
• Contribute to a mission to simplify the customer journey, reduce avoidable call volume, and improve call center efficiency by turning unstructured customer interactions into structured, actionable intelligence.

• Direct change management activities and initiatives in collaboration with Raytheon DT organization leadership.
• Communicate goals based on organizational objectives.
• Align change advice and consultancy resources to organizational needs.
• Build change capability and maturity by providing training, communications and growing change advocacy within the broader organization.
• Create change management strategy for enterprise level initiatives and the application of a structured methodology, including leading change management activities, assessing change impact, user readiness, and communication strategy.

Data & AI Change Manager

• Ensure quality and data reconciliation
• Attend and participate in sponsor meetings
• Manage all data management deliverables for assigned studies
• Keep supervisor informed of project status
• Review data and identifying errors/inconsistencies
• Collaborate with appropriate project team to resolve data issues
• Track outstanding issues and following-up until resolution
• Ensure accuracy in manipulation and scrutiny of clinical data

Clinical Data Manager

• Lead conversations about our metrics and dashboards, and leverage multi-sourced data and analytics principles to give answers to our team on how we can optimize our data and programs
• Understand the connection between all of our data sources and how to pull them together in fact and dimension models
• Build and cultivate a positive relationship between teams where metrics and goals are aligned
• Provide data-driven recommendations to help teams across the business be more efficient and successful

Principal, Central Analytics Lead

• Independently perform tasks to support the development of analytical solutions
• Develop domain and business knowledge to build statistical models.
• Communicate analysis, insights, and results to manager, peers, and working team.
• Assist or mentor less experienced analytic talent.
• Perform other duties as assigned.

Sr. Associate Data Scientist – Data Science Leadership Development Program

• Assisting to design, develop and program methods, processes, and systems to consolidate and analyze unstructured and structured data sources
• Providing recommendations on projects that deal with data science related concepts
• Designing and building statistical models, analyses at the right level of complexity to produce relevant results for the business
• Identifying, integrating and structuring complex data flows
• Validating, manipulating and performing data analysis tasks
• Providing qualitative and quantitative data support to ensure accuracy of metrics
• Performing other duties as assigned

Data Science Leadership Development Program Intern

• Perform tasks to support the development of analytical solutions following defined processes.
• Learn domain and business knowledge to perform assigned steps to build statistical models.
• Communicate analysis, insights, and results to manager and working team.
• Develop your understanding of key business areas (e.g., product, enterprise, industry, claim process and competitors) that enable project work.
• Perform other duties as assigned.

Data Scientist – Leadership Development Program Associate

• The program is multi-faceted and offers a business insights & analytics and business development curriculum focused on analytics, insurance, strategy, leading self and influencing others.
• Other program components include formal mentoring, networking, and career guidance.
• Please note that occasional travel for business meetings and events is an expectation of program participants.
• Participants could be placed in one of the following rotations: Business Performance Analytics, Data Engineering, Business Insights Delivery, Data Management, Decision Science.
• Answer business questions, test hypotheses, and assess impacts/results through diagnostic analysis and active monitoring.

Business Insights & Analytics Leadership Development Program Participant

• Advise clients on end-to-end solutions across data strategy, data management, and data quality.
• Support business development, methodology development, team leadership, and delivery execution for data governance assessments and implementations.
• Design and develop data governance technology solutions across data quality, data dictionaries, business glossaries, data standards, and data policies.
• Define organizational design, governance processes, policies, roles, responsibilities, success metrics, and operating models for client data programs.
• Build roadmaps covering technology, culture, governance, processes, skills, competencies, data quality, analytics, and data management maturity.
• Lead and collaborate with data governance teams to create business cases, resource plans, implementation roadmaps, and enterprise data system assessments.
• Assess current-state environments, identify client pain points and requirements, and help define a practical vision and strategy for becoming a data-driven organization.
• Advise clients as a trusted partner and provide thought leadership on data governance, data management, cloud transformation, AI readiness, and related best practices.
• Manage resources, budgets, project delivery, team development, training, mentoring, and performance assessment.

Data Strategy and Governance Manager

• Provide leadership to managers and supervisors for all daily operations of AVANGRID Networks Energy Control Centers.
• Responsible for maintaining the safety, reliability, and security of the Company's electric and gas transmission and distribution systems.
• Oversee the use of the Energy Control System (ECS) and Gas SCADA System.
• Develops departmental goals related to corporate goals and objectives.
• Lead the design and development of advanced ML/AI solutions (GenAI, LLMs, NLP, classical ML, causal inference) that directly support Avangrid Networks’ customer experience priorities: CSAT improvement, payment and collections, and contact deflection.
• Architect end-to-end ML systems on modern cloud platforms (Azure, Databricks), including feature stores, model registries, deployment pipelines, monitoring, and retraining workflows - establishing reference patterns for the broader Data Science & Analytics organization.
• Lead GenAI and agentic AI initiatives for both customer-facing (self-service) and agent-assist applications, including RAG architectures, retrieval pipelines, evaluation frameworks, and responsible AI guardrails for the flagship Iberdrola initiatives.
• Partner closely with Data Engineering to define data product requirements, drive customer-oriented data infrastructure build-out, and ensure analytics-ready datasets across SAP, CC&B, AMI, contact center, and digital platforms.
• Collaborate closely with technical leads in Customer Service, Elec/Gas Operations, Digital Platforms, Regulatory, and IT to translate business needs into AI/ML solutions and embed them into production workflows.
• Serve as the data domain expert (“Lead SME”) for customer, billing, contact, and consumption datasets—including data lineage, quality, and appropriate analytical use.
• Serve as technical lead and mentor for junior data scientists and analysts; review modeling approaches, code, and methodology; raise the technical bar across the team.
• Support regulatory filings, audits, rate cases, and PSC/DPU inquiries by delivering accurate, defensible, data-driven analysis and written narratives.
• Champion responsible AI practices, including model documentation, bias assessment, privacy compliance, and alignment with Avangrid’s AI governance and Global AI Inventory standards.

Principal, Data Science – Architecture

• provide and maintain effective material orders
• customer service
• inventory management
• oversee loading and unloading of inbound and outbound freight
• perform quality checks on freight
• execute daily inventory cycle counts
• process return shipments
• oversee placement of server racks
• install cabling in server racks
• operate material handling equipment
• perform cleanup activities in the work area

Data Center Lead

• Oversee loading and unloading of inbound and outbound freight
• Perform quality checks on inbound and outbound freight
• Execute daily inventory cycle counts and replenishment orders
• Process return shipments of various electronic components
• Oversee and perform the placement server racks on the datacenter floor
• Oversee and perform the population of electronic components and install cabling into server racks
• Install rack hardware using various hand, power and measuring tools
• Operate various types of material handling equipment
• Perform and oversee cleanup activities in the work area

Data Center RMA Team Lead

• Oversee loading and unloading of inbound and outbound freight
• Perform quality checks on inbound and outbound freight
• Execute daily inventory cycle counts and replenishment orders
• Process return shipments of electronic components
• Oversee and perform the placement of server racks
• Install rack hardware using various tools
• Operate material handling equipment
• Perform and oversee cleanup activities to ensure safety

Data Center Dock Team Lead – Monday-Thursday, 2:00 PM - 12:00 AM

• Own HR data management at Rakuten
• Manage the data governance framework for all Workday employee data
• Lead, develop, and retain a team of HR data management professionals
• Own the HR data workstream for recurring high-stakes programs
• Champion automation and AI adoption within HR Data Management
• Serve as a strategic partner to HR, Payroll, Global Total Rewards, Finance, Legal, IT, and HRIS

Manager, HR Data Management

• Lead the design and delivery of advanced data science solutions that align to business and clinical priorities
• Develop and deploy predictive models, machine learning solutions, and AI capabilities to drive measurable outcomes
• Translate complex data into clear insights and recommendations for business and technical stakeholders
• Partner with cross-functional teams (IT, Clinical, Operations) to deliver end-to-end analytics solutions
• Apply advanced analytical methods including segmentation, regression, and time-series analysis to solve business problems
• Create scalable data pipelines and leverage big data technologies to support analytics initiatives
• Present findings to senior leaders to influence strategy and decision-making
• Provide thought leadership and mentor others on data science best practices and emerging technologies

Data Science Advisor

• Own the data science and applied AI roadmap for operations—agentic systems, forecasting, lead scoring, voice of the customer aggregation, and decision-support that improve throughput, reliability, and unit economics.
• Build agents and AI workflows that don't just predict but act.
• Own the data science and AI behind post-sales product experiences, including the support agent, onboarding intelligence, and customer success automation—from design through production deployment, evaluation, and quality monitoring.
• Lead, hire, and develop a data science team executing on operational and product-facing work; set standards for technical rigor, evaluation, and production quality.
• Partner with operations, finance, and product leadership to identify high-leverage problems, frame them, and translate them into operational decisions and shipped AI capabilities.
• Drive the full lifecycle from problem definition through deployment and monitoring, ensuring systems hold up in production—whether powering an internal forecast, an autonomous workflow, or a live customer interaction.
• Establish metrics and evaluation frameworks connecting this work to operational, financial, and customer outcomes (e.g., deflection, resolution quality, time-to-value, retention), including rigorous evaluation of non-deterministic AI systems.
• Collaborate with data engineering, machine learning engineering, platform, and product teams on the infrastructure, data quality, orchestration, tooling, and guardrails these systems depend on.
• Communicate findings and recommendations to executive stakeholders, balancing technical depth with business clarity.
• Champion an AI/agent-first way of working within the team—both as a hands-on technical leader (e.g., Claude Code) and by inventing agentic systems that make the team faster.

Data Scientist jobs in Connecticut

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Staff Data Product Manager

Data Science Manager

Data Scientist

Program Manager, Data and Information Governance

Data Scientist

Data & AI Change Manager

Clinical Data Manager

Principal, Central Analytics Lead

Sr. Associate Data Scientist – Data Science Leadership Development Program

Data Science Leadership Development Program Intern

Data Scientist – Leadership Development Program Associate

Business Insights & Analytics Leadership Development Program Participant

Data Strategy and Governance Manager

Principal, Data Science – Architecture

Data Center Lead

Data Center RMA Team Lead

Data Center Dock Team Lead – Monday-Thursday, 2:00 PM - 12:00 AM

Manager, HR Data Management

Data Science Advisor

Director, Data Science