Data Scientist

• Lead the delivery of enterprise data products that power analytics, operational decision-making, AI initiatives, and customer-centric business capabilities
• Develop and maintain a multi-year roadmap for assigned data products
• Establish trusted partnerships with business leaders, data owners, and technology teams
• Own and manage the data product backlog
• Ensure compliance with MAPFRE data governance standards
• Perform deep analysis of business processes, data flows, and operational challenges
• Manage the lifecycle of enterprise data products from ideation through retirement

Data Product Manager II

• Own and execute the global sourcing process, systems, and analytics strategy across GE Vernova
• Define and drive the Source‑to‑Pay future‑state operating model, ensuring simplification, standardization, scalability, and strong governance
• Lead enterprise sourcing transformation programs from concept through execution, with measurable business outcomes
• Conduct sourcing maturity assessments across Business Units and lead targeted improvement roadmaps
• Own and evolve the global sourcing systems landscape, including platforms such as SupplierConnect, Sourcegate+, Grid Fusion VMR, Sourcing360, and ERP integrations
• Lead sourcing data ingestion into the enterprise data lake; define common metrics, dashboards, and insights
• Build scalable analytics capabilities to improve decision‑making, savings identification, compliance, and risk visibility
• Define and execute the digital and GenAI roadmap for sourcing, from use‑case identification through deployment and adoption
• Partner with IT, finance, legal, and external vendors to modernize sourcing tools and workflows
• Drive user adoption, change management, and capability building to fully capture technology value
• Lead high‑visibility sourcing initiatives, including: GenAI applications, risk management programs, commodity and category playbooks, should‑costing, and productivity initiatives
• Own CPO‑level governance, including Sourcing Councils, leadership operating rhythms, and enterprise reviews
• Prepare executive‑ready materials for ELT, Board, and senior leadership forums
• Lead, coach, and develop a global team responsible for sourcing transformation, systems, and analytics
• Drive enterprise capability‑building programs (digital, GenAI, sourcing foundations, analytics fluency)
• Embed Lean, Kaizen, and continuous improvement principles across sourcing teams
• Foster a culture of accountability, data‑driven decision making, and innovation

Global Sourcing Systems, Initiatives & Advanced Analytics Leader

• 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

• Drive key components of the strategy for the Finance Data Platform team
• Manage the lifecycle of how massive data volumes are sourced and published for Finance consumption
• Collaborate with engineering and data analysts

Manager, Product Management – Finance Data

• You'll own the research that helps define our AI Shopping roadmap
• Helping shape how we measure a brand's AI Shopping capability
• Optimizing for the best outcomes
• Designing the studies, building the models, publishing the findings
• Sitting with customers to show them what the data means for their business

Senior Data Scientist, AI Search / AEO Research

• Evaluate open-source and internally-developed modeling and analytics tools using real business data
• Integrate internal data with external data sources and APIs to discover and implement actionable insights
• Design and craft data science models to communicate solutions to customers and company leadership

Data Science Internship

Data Science Intern

• Develop and execute sales strategies to achieve company revenue targets and expand client base within the data center power infrastructure sector.
• Conduct thorough market research to identify potential clients, industry trends, and competitive landscape across the data center and critical power supply chain (hyperscalers, colocation providers, utilities, and EPC firms).
• Identify, target, and acquire new clients among data center operators, hyperscalers, colocation providers, and the utilities/EPCs that build and power their campuses.
• Build and maintain relationships with key decision-makers and stakeholders — including facilities, electrical engineering, and reliability teams — within target organizations.
• Lead and manage the entire sales cycle, from initial contact to sales negotiations and closure, working together with the Power and Industrial sales teams.
• Attend industry conferences, trade shows, and networking events to promote products and services and establish industry connections.
• Develop and nurture long-term relationships with clients to ensure customer satisfaction and repeat business.
• Prepare and deliver compelling presentations, proposals, and product and technology demonstrations to prospective clients.
• Collaborate with the global marketing team to develop sales materials, case studies, and other promotional content.
• Work closely with the global product management and development, regional marketing, and customer support teams to ensure alignment and support for business development activities.
• Monitor and report on sales metrics, pipeline status, and business development activities.
• Analyze and assess the effectiveness of business development strategies and make data-driven recommendations for improvement.

Business Development Manager, Data Center Power

• 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

• Work as part of a team to build predictive models and applied LLMs designed to support the Kemper claims operation in areas such as fraud detection, subrogation identification, vehicle damage severity, adjuster triage and claims quality management.
• Develop and automate predictive modeling processes that can be deployed through the organization to solve reoccurring analytics needs.
• Contribute to the improvement of internal modeling capabilities and data infrastructure by suggesting and applying tweaks to existing processes.
• Monitor deployed solutions and escalate as needed.

• Be a hands-on scientific and technical leader, leading a portfolio of RWE projects, developing best practices, and mentoring team members.
• Identify common technical requirements for RWE projects, develop and maintain a common suite of tools that enable RWE data scientists to accelerate project delivery.
• End-to-end expertise in RWE studies including conceptualizing research questions, data feasibility, study design, analysis, programming, and interpretation.
• Provide thought leadership and hands-on programming expertise for developing and applying Real-World Data (“RWD”) methodologies to mitigate observed and unobserved biases in the execution of external control arm studies, hybrid control studies, comparative effectiveness analyses, etc.
• Provide thought leadership and hands-on programming expertise to generate actionable insights from post-hoc RCT analyses, observational databases, and literature reviews to support regulatory agency interactions.
• Independently create study protocols, statistical analysis plans, and statistical programming deliverables including analysis-ready data, tables and figures
• Partner with the Data Science Therapeutic Area scientists to conceptualize, lead, shape and deliver Real World Evidence

Senior Principal Scientist, Data Science RWE

• Lead operational planning and execution of the enterprise AI Literacy strategy across multiple geographies and business functions.
• Develop and maintain scalable operating models, governance structures, processes, and delivery frameworks supporting AI Literacy initiatives.
• Manage the end-to-end delivery of virtual and in-person AI Literacy learning programs for approximately 15000 employees globally.
• Coordinate schedules, timelines, resources, dependencies, and implementation activities across multiple workstreams.
• Manage external vendors, agencies, and contractors responsible for training delivery and operational support.
• Monitor vendor performance, contractual obligations, service levels, and delivery outcomes.
• Manage program budgets, forecasts, resource plans, and operational expenditures.
• Drive continuous improvement initiatives focused on operational efficiency, scalability, and cost effectiveness.
• Implement processes and controls that support sustainable growth of the AI Literacy program.
• Lead continuous improvement efforts through data-driven decision making and performance analysis.

Director, R&D Data Science – Operations & Community Lead

• Be a hands-on scientific and technical leader, leading a portfolio of RWE projects, developing best practices, and mentoring team members.
• Identify common technical requirements for RWE projects, develop and maintain a common suite of tools that enable RWE data scientists to accelerate project delivery.
• End-to-end expertise in RWE studies including conceptualizing research questions, data feasibility, study design, analysis, programming, and interpretation.
• Provide thought leadership and hands-on programming expertise for developing and applying Real-World Data (“RWD”) methodologies to mitigate observed and unobserved biases in the execution of external control arm studies, hybrid control studies, comparative effectiveness analyses, etc.
• Provide thought leadership and hands-on programming expertise to generate actionable insights from post-hoc RCT analyses, observational databases, and literature reviews to support regulatory agency interactions.
• Independently create study protocols, statistical analysis plans, and statistical programming deliverables including analysis-ready data, tables and figures.
• Partner with the Data Science Therapeutic Area scientists to conceptualize, lead, shape and deliver Real World Evidence.

• Responsible for end-to-end delivery of data management services
• Collaborate with internal and external customers
• Ensure staff deliver high quality, timely service and meet all regulatory requirements
• Hire, manage staff performance, utilization, retention, process improvements
• Financial management for assigned projects

Manager, Clinical Data Management

• Partner with cross-functional teams to define a neuropsychiatric digital health roadmap that integrates AI/ML (e.g., foundation models), data science, and company priorities across the patient journey, ensuring clinical relevance and patient-centered outcomes.
• Monitor emerging technologies in neuropsychiatry, digital phenotyping, remote assessment, passive sensing, and speech and language analytics to bring forward next-generation solutions for neuropsychiatry R&D.
• Execute the neuropsychiatry-focused digital health strategy by applying AI/ML, modeling, and longitudinal analytics to support patient stratification, endpoint development, and clinical trial optimization, in partnership with disease experts, statisticians, and platforms and clinical teams on study design and validation of digital measures, balancing their informativeness with low clinical burden for patients and study teams.
• Develop and apply sophisticated statistical/ML/AI models using digital health data to generate insights into disease and treatment outcomes.
• Develop multimodal approaches combining digital health data with imaging, blood-based biomarkers, omics, and real-world data to provide a more holistic picture of patients suffering from neuropsychiatric disease.
• Contribute to evidence packages to support regulatory qualification of digital endpoints and tools.
• Ensure validation and compliance with evolving global regulatory and data privacy standards.
• Collaborate with clinical operations to integrate digital health technologies into trial design, working cross-functionally to optimize data capture, integration, and interoperability of digital solutions.
• Partner with regulatory and medical affairs to build external collaborations with academic groups, technology partners, regulators, health authorities, and payers to advance digital health standards and novel endpoints.

Senior Manager, R&D Data, Data Science, AI – Digital Health for Neuropsychiatry

• Partner with cross-functional teams to define a neuropsychiatric digital health roadmap that integrates AI/ML (e.g., foundation models), data science, and company priorities across the patient journey, ensuring clinical relevance and patient-centered outcomes.
• Monitor emerging technologies in neuropsychiatry, digital phenotyping, remote assessment, passive sensing, and speech and language analytics to bring forward next-generation solutions for neuropsychiatry R&D.
• Execute the neuropsychiatry-focused digital health strategy by applying AI/ML, modeling, and longitudinal analytics to support patient stratification, endpoint development, and clinical trial optimization, in partnership with disease experts, statisticians, and platforms and clinical teams on study design and validation of digital measures, balancing their informativeness with low clinical burden for patients and study teams.
• Develop and apply sophisticated statistical/ML/AI models using digital health data to generate insights into disease and treatment outcomes.
• Leverage longitudinal disease modeling, Bayesian methods, and causal inference techniques to inform decision-making.
• Develop multimodal approaches combining digital health data with imaging, blood-based biomarkers, omics, and real-world data to provide a more holistic picture of patients suffering from neuropsychiatric disease.
• Contribute to evidence packages to support regulatory qualification of digital endpoints and tools.
• Ensure validation and compliance with evolving global regulatory and data privacy standards.
• Collaborate with clinical operations to integrate digital health technologies into trial design, working cross-functionally to optimize data capture, integration, and interoperability of digital solutions.
• Partner with regulatory and medical affairs to build external collaborations with academic groups, technology partners, regulators, health authorities, and payers to advance digital health standards and novel endpoints.

• Lead a team within the Transfer Agency
• Ensure accurate, timely, and efficient delivery of data reporting to both internal stakeholders and external clients
• Build and maintain advanced Excel data models using Power Pivot and the Excel Data Model
• Create DAX measures, calculated columns, and KPIs for business reporting
• Use Power Query to automate data extraction, transformation, and consolidation from multiple sources
• Develop interactive dashboards and executive reports in Excel
• Improve existing spreadsheets by increasing automation, accuracy, and efficiency
• Troubleshoot and optimize complex Excel workbooks
• Integrate data from databases, flat files, APIs, and other systems
• Identify opportunities to automate manual reporting and business processes

Manager, Data Reporting

• own multiple concurrent projects across model development, strategic analysis, and analytics product delivery — framing the business question, designing the approach, building the solution, and presenting findings to senior stakeholders (Lead Director, Executive Director, AVP)
• set technical direction for your workstream, mentor junior data scientists, and partner directly with business leaders across sales, underwriting, and finance to turn analysis into action

Senior Data Scientist

• Lead the design and development of scientifically rigorous analytics solutions leveraging Power Factors' extensive operational data
• Collaborate closely with software development teams, product management, and technically sophisticated customers to translate real-world operational challenges into robust analytical solutions
• Identify, evaluate, and prioritize high-impact advanced analytics opportunities focused on BESS performance, health, and revenue optimization
• Lead the development of advanced data science solutions from concept through production deployment
• Engage directly with technically sophisticated customers to explain analytical methods, assumptions, and results with clarity and precision
• Serve as an internal BESS subject matter expert, supporting product, sales, and customer success teams with domain guidance
• Stay current with advances in battery science, electrochemical modeling, grid storage economics, and ML for energy systems

Data Scientist jobs in Massachusetts

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Data Product Manager II

Global Sourcing Systems, Initiatives & Advanced Analytics Leader

Data Science Manager

Manager, Product Management – Finance Data

Senior Data Scientist, AI Search / AEO Research

Data Science Internship

Data Science Intern

Business Development Manager, Data Center Power

Data Scientist

Data Scientist

Senior Principal Scientist, Data Science RWE

Director, R&D Data Science – Operations & Community Lead

Senior Principal Scientist, Data Science RWE

Director, R&D Data Science – Operations & Community Lead

Manager, Clinical Data Management

Senior Manager, R&D Data, Data Science, AI – Digital Health for Neuropsychiatry

Senior Manager, R&D Data, Data Science, AI – Digital Health for Neuropsychiatry

Manager, Data Reporting

Senior Data Scientist

Senior Data Scientist