Data Scientist

• Frame ambiguous revenue-cycle problems as tractable modeling problems and own them end to end such as claim and invoice viability scoring, denial and underpayment prediction, revenue/ARR prediction, and work prioritization from hypothesis to a validated, monitored result in production
• Build and validate models with statistical rigor: thoughtful feature design, sound handling of missingness and class imbalance, calibration, honest evaluation against simple baselines, and a clear treatment of uncertainty
• Design, build, and maintain the data pipelines feeding these models integrating with source collections, billing, and EHR systems and internal data stores, and handling data collection, cleansing, field mapping, and payer/plan normalization with a bias toward reliability and data quality
• Establish and own MLOps practice: model monitoring and drift detection (e.g., population stability), calibration and threshold selection, benchmarking against simple baselines, explainability (e.g., SHAP and interpretable coefficients), experiment and version tracking, and model documentation such as model cards
• Partner with subject-matter experts to encode business-rule and heuristic logic alongside statistical models where that produces a more accurate or more defensible result
• Gather and document business requirements for revenue-cycle initiatives, including workflows, decision points, stakeholder objectives, operational constraints, success criteria, data availability, and underlying business assumptions, and maintain traceability as those requirements evolve.

Senior AI Data Scientist

• Design and implement statistical and machine learning models for time-series forecasting, anomaly detection, and asset health scoring across utility networks.
• Build and maintain end-to-end ML pipelines on Databricks from feature engineering and model training to validation, deployment, and monitoring in production.
• Apply classical statistical methods (GLMs, GAMs, mixed-effects models, Bayesian inference) alongside modern ML techniques (ensemble approaches, network analysis, neural networks) to solve grid operations problems.
• Develop predictive maintenance and degradation models for utility infrastructure using telemetry and SCADA data at scale.
• Translate ambiguous business problems into well-defined modeling problems with appropriate statistical frameworks - e.g., knowing when a LM/GLM is sufficient and when gradient boosting or deep learning is warranted.
• Implement model monitoring, drift detection, and automated retraining workflows to maintain model performance over time.
• Contribute to load forecasting, demand response optimization, and outage prediction systems.
• Ensure model interpretability and explainability for utility stakeholders and regulatory compliance.
• Contribute to internal knowledge-sharing on statistical best practices.

• Analyze large, complex fraud datasets to identify patterns, trends, and anomalies that inform detection strategies and business decisions
• Evaluate existing static, rule-based fraud detection systems through data-driven assessments of their performance and coverage, and deliver clear, prioritized recommendations for rule updates, retirement, or new rule creation
• Partner with fraud operations teams to understand frontline detection challenges and translate operational insights into analytical hypotheses and actionable solutions
• Utilize AI-assisted development tools such as Amazon Q and Kiro to accelerate analytical workflows and solution delivery
• Prototype and contribute to the development of agentic AI applications leveraging AWS AgentCore and generative AI solutions that advance the team's fraud strategy capabilities
• Collaborate with fraud technology teams to ensure models, rules, and AI-driven outputs are implemented accurately and monitored effectively within the AWS production environment
• Design, build, and validate machine learning and statistical models to enhance fraud detection capabilities, improve precision and recall, and reduce false positive rates
• Monitor deployed models and fraud rules on an ongoing basis, identifying performance degradation or emerging detection gaps that require intervention
• Communicate findings, model results, and strategic recommendations clearly to both technical and non-technical stakeholders
• Stay current with emerging trends in fraud typologies, financial crime, and AI and machine learning developments within the AWS ecosystem, and bring relevant innovations back to the team

Lead Data Scientist – Gen AI Lead

• Manage a group or process(potentially global)
• Work with business data users to define the use of data within risk systems
• Recommend remediation of control gaps and implements effective risk controls
• Participate in and lead user acceptance testing of data control processes
• Ensure the completeness, validity, and accuracy of data on a daily basis
• Lead cross functional strategic efforts to remediate data quality issues
• Evaluate existing GRM data architecture and design solutions to simplify and optimize the data environment
• Participate in building the business cases required to secure approval and funding for the Data and Analytical efforts

Data Support Manager

• Project Leadership & Delivery
• Lead data-related projects end-to-end: scoping, planning, execution, and delivery
• Build and own project plans, timelines, budgets, and resource allocation across workstreams
• Establish and refine project operating mechanisms -- status cadences, intake processes, and launch readiness criteria
• Remove blockers and make decisions at the pace the project needs to maintain momentum
• Hold workstreams accountable to delivery timelines while protecting space for necessary discovery
• Drive go/no-go decisions for major project milestones and data platform changes
• Data Strategy & Prioritization
• Help shape the organization's data roadmap, prioritizing initiatives based on business value and impact
• Translate business objectives into data project priorities, working with leadership to align investments with strategic goals
• Conduct landscape and options analysis to inform build-vs-buy and tooling decisions from a business-outcomes perspective
• Own the narrative -- communicate project strategy, progress, and outcomes to leadership through status updates and planning documents
• Stakeholder Management & Organizational Influence
• Serve as the primary point of contact between data teams, compliance, engineering, and business stakeholders
• Build and maintain trusted relationships with cross-functional partners; represent project priorities in stakeholder forums
• Manage up effectively -- proactively surface risks, trade-offs, and resource constraints to leadership with recommended paths forward
• Drive alignment across competing organizational needs through influence, data, and clear communication
• Data Governance & Compliance
• Ensure projects adhere to data governance policies, including data quality, access control, retention, and privacy standards
• Partner with data teams and compliance to align project deliverables with governance frameworks (e.g., GDPR, HIPAA, SOC 2, or internal data policies)
• Guide decisions on data ownership, stewardship, and classification across project workstreams
• Ensure the project maintains compliance with organizational data standards and partners effectively with legal and security teams as needed
• Risk Management & Reporting
• Proactively identify risks and dependencies, and drive mitigation plans before they threaten delivery
• Track and report on project and data governance metrics adoption, data quality issues, policy exceptions as part of regular reporting
• Manage scope and change requests, balancing stakeholder needs against delivery constraints

Project Manager, Data Strategy

• 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.

• Own retailer onboarding from kickoff through go-live.
• Manage weekly scan data submission health across the full retailer base.
• Serve as the primary point of contact for all retailer and CPG partner communications.
• Publish the weekly health dashboard for program performance.
• Coordinate with Scan Data Engineering to ensure technical setup and test submissions are completed.
• Monitor each submission cycle and communicate directly with retailers on action items.

Data Programs Manager

• Lead complex initiatives related to business analysis, including those that are cross functional, with broad impact, and act as key participant in data aggregation, monitoring, and reporting of stress testing and monthly loss forecast for Risk Analytics.
• Collaborate with stakeholders and business partners to identify requirements, drive process and technology improvements, and ensure compliance with Finance and Risk governance frameworks, controls, and documentation requirements
• Support end-to-end implementation activities, including test planning and execution, documentation updates, stakeholder support, issue resolution, and post-implementation operational readiness.
• Review and analyze data to provide results specific to businesses supported.
• Make decisions in complex product strategies and risk exposure, requiring solid understanding of business unit projects and regulatory responses, policies, procedures, and compliance requirements that influence and lead Analytic and Reporting to meet deliverables and drive new initiatives.
• Collaborate and consult with peers, less experienced to more experienced managers, to resolve production, project, and regulatory issues, and achieve risk analytics goals.
• Lead projects, teams, and mentor.

Lead Risk Analytics Consultant – Corporate Credit Risk Oversight, Allowance

• Implements complex projects for institutional retirement plans with high quality data outcomes
• Advises on data solutions regarding complex plan administration challenges
• Resolves risks and issues for complex retirement plan implementations in a timely manner
• Engages and leads appropriate resources in a highly-matrixed environment to resolve data issues
• Guides less experienced team members regarding retirement plan transition challenges that require more advanced knowledge
• Ensures internal tools and procedures are updated based on new learnings

Transitions Data Lead II

• Own the vision, roadmap, and lifecycle of data products
• Partner with IT leaders, analytics teams, and data engineers to translate business needs into clear product requirements and prioritized backlogs
• Drive standardization of key metrics and definitions to enable consistent, decision‑ready insights across IT
• Ensure data products meet enterprise standards for quality, security, governance, and auditability
• Lead cross‑functional delivery from discovery through production, including release planning and ongoing optimization
• Measure and drive adoption, usage, and value realization of data products
• Communicate product strategy, progress, and insights to IT executive stakeholders and senior management
• Continuously improve data product ways of working, leveraging agile and product management best practices

Senior Data Product Manager

• Represent Supply Chain on the global platform management team, helping shape program scope to align with global sourcing strategies and preferred supplier partnerships.
• Lead end-to-end supply chain planning for new product launches, from concept development through production ramp-up.
• Partner with engineering and product teams to translate design requirements into scalable manufacturing and sourcing strategies.
• Drive cross-functional alignment across procurement, manufacturing, quality, and logistics to support launch readiness and execution.
• Optimize inventory requirements by analyzing customer forecasts, bills of material, and supplier lead times to support production needs.
• Drive material and supply chain readiness for New Product Introduction (NPI) builds, from concept phase through production handoff.
• Collaborate with sourcing leads to ensure program contracts and inventory stocking agreements support market lead-time requirements, program milestones, and production launch needs.
• Partner with Supplier Readiness and Supplier Development teams to ensure supplier capacity supports rapid Data Center growth.

Senior Manager, Supply Chain Program Manager – Data Centers

• Maximize value for products
• Work with stakeholders to understand needs
• Ensure product delivery meets client expectations
• Define data domain-level strategies
• Establish consistent data flow design patterns
• Develop business cases for new products and features
• Lead governance routines and architectural vision

Data Product Manager – Strategy Lead

• Define target-state models for new data sources
• Ensure models are scalable + reusable across products
• Apply enterprise data management policy and drive model standardization across domains
• Evaluate impact of data model changes across regulatory reporting, analytics, and operations
• Serve as a strategic liaison between data management, product teams, data engineering, and architecture teams throughout the data product lifecycle
• Provide vision, direction, and expertise to senior leadership on implementing innovative and significant data product solutions that are large-scale cross-functional or companywide strategies
• Lead complex data product initiatives, delivering scalable solutions aligned to data governance standards; perform deep dives into current data models to understand structure and define target-state design while guiding cross-functional teams
• Provide expert input on new use case intake, prioritization, product roadmap definition, and other critical business processes
• Lead end-to-end data projects, from requirement gathering to solution delivery
• Design and implement scalable data models, pipelines, and governance frameworks
• Provide thought leadership on data strategy, architecture, and emerging technologies
• Collaborate with cross-functional teams (Business, Technology, Operations) to align analytics solutions with organizational goals
• Ensure compliance with data security, privacy, and regulatory standards

Senior Lead Data Product Management Consultant – Auto Data & Insights

• Develop and implement NLP, LLM, and generative AI approaches (e.g., RAG, prompt strategies).
• Define agentic workflows and reasoning strategies for multi-step legal tasks.
• Develop retrieval strategies, including hybrid search (semantic + lexical), and evaluation metrics (e.g., relevance, ranking quality).
• Analyze large-scale legal datasets to extract insights and improve model performance.
• Establish best practices for model evaluation, validation, and benchmarking.
• Translate experimental results into clear product recommendations and business impact.
• Collaborate with product, legal experts, and engineers to align solutions with user needs.
• Mentor team members and provide technical leadership in data science and AI.

Senior Data Scientist II

• Drive the development of innovative AI based solutions for enterprise stakeholders
• Translate business needs into AI solutions that align with strategic goals
• Design and build best-in-class AI and agent evaluation capabilities
• Deliver the analytical solution to complex business problems
• Document objectives, assumptions and processes

Senior Data Scientist – AI Services, Platforms

• Build and execute partner plans aligned to Intapp's growth priorities and the partner program — joint value propositions, multi-year collaboration roadmaps, co-innovation agendas, joint go-to-market, and co-selling.
• Translate market and client needs into joint solutions — working with Product, R&D, and Industries to develop data integrations and vertical-AI capabilities that make Intapp solutions, including Celeste, measurably smarter and more firm-specific.
• Drive data and interoperability — enable third-party data integration with Celeste via MCP and agent-to-agent integration, and structure fit-for-purpose commercial mechanics.
• Own and grow executive relationships with assigned partners as their trusted advisor and strategic liaison across Intapp.
• Report on execution and results — partner-sourced, -influenced, and -product revenue, integration certifications, and co-innovation outcomes.
• Engage in client opportunities and sales cycles where partners strengthen our positioning, complete the solution, or open access to key stakeholders.
• Operate the coopetition and governance framework — qualify product partnerships with senior executives across Intapp and facilitate decisions.
• Advance partner mindshare and capability — enablement, integration certifications, and investment in Intapp solutions across partner organizations.
• Anchor the operating rhythm — embed partner plans in the annual and strategic plans of our business units, R&D, and GTM functions, and keep Partner Operations systems current.
• Serve as a thought partner to the wider Alliances & Partners team, contributing to ecosystem strategy, executive partner briefings, and the continuous evolution of Intapp's partner program.

Senior Partner Development Manager, Vertical AI & Data Partners

• Lead a critical portion of IQVIA Digital's measurement portfolio
• Oversee products and services that enable our measurement value proposition
• Maximize the value, adoption, scalability, and commercial success of measurement solutions
• Collaborate with cross-functional teams to define product strategy

Senior Product Manager, Measurement Studies, Platforms & Data Services

• Advise line of business and companywide functions on business strategies based on research of performance metrics, trends in population distributions, and other complex data analysis to maximize profits and asset growth, and minimize operating losses within risk and other operating standards
• Provide influence and leadership in the identification of new tools and methods to analyze data
• Ensure adherence to compliance and legal regulations and policies on all projects managed
• Provide updates on project logs, monthly budget forecasts, monthly newsletters, and operations reviews
• Assist managers in building quarterly and annual plans and forecast future market research needs for business partners supported
• Strategically collaborate and consult with peers, colleagues, and mid-level to senior managers to resolve issues and achieve goals
• Lead projects, teams, or serve as a peer mentor to staff, interns and external contractors

Lead Analytics Consultant

• Build and lead a team focused on building, consolidating, and integrating a data warehouse that will support the Wealth Management line of business
• Meet regularly with business stakeholders to understand business context and inform on strategy
• Build meaningful relationships with relevant stakeholders and effectively partner to remove organizational obstacles and guide cross-team strategic efforts
• Act as agile/product champion by enabling product teams and partnering with other leaders to drive empowerment, autonomy, engineering momentum, and business value
• Foster a culture of empowerment, engineering excellence, and growth

Data Scientist jobs in North Carolina

See all jobs on JobTailor

Senior AI Data Scientist

Data Scientist

Lead Data Scientist – Gen AI Lead

Data Support Manager

Project Manager, Data Strategy

Data Scientist

Data Scientist

Data Programs Manager

Lead Risk Analytics Consultant – Corporate Credit Risk Oversight, Allowance

Transitions Data Lead II

Senior Data Product Manager

Senior Manager, Supply Chain Program Manager – Data Centers

Data Product Manager – Strategy Lead

Senior Lead Data Product Management Consultant – Auto Data & Insights

Senior Data Scientist II

Senior Data Scientist – AI Services, Platforms

Senior Partner Development Manager, Vertical AI & Data Partners

Senior Product Manager, Measurement Studies, Platforms & Data Services

Lead Analytics Consultant

Data Integration Manager