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

• Build and maintain strong relationships with internal and external stakeholders to develop and execute comprehensive project plans aligned with business and product objectives.
• Define project scope, goals, deliverables, success criteria, and business outcomes in partnership with key stakeholders.
• Lead end-to-end delivery of complex IT and Data Platform projects from planning and execution through governance, monitoring, and successful operational handoff.
• Develop and manage integrated project plans, schedules, budgets, resource plans, forecasts, milestones, dependencies, and risk registers.
• Partner with business stakeholders to balance requirements, priorities, costs, resources, and delivery trade-offs while identifying win-win solutions.
• Ensure adherence to project governance standards, raising risks and issues to management and stakeholders as required.
• Apply Agile methodologies to project delivery by coordinating sprints, iterations, and incremental product value delivery.
• Deliver projects within agreed scope, quality, timeline, budget, and customer expectations.
• Identify, assess, and mitigate project risks while developing contingency plans and maintaining comprehensive risk registers.
• Manage project change requests, approvals, documentation, meeting minutes, and decision traceability in accordance with governance standards.
• Oversee third-party supplier engagements, including contract negotiations, performance management, and accountability for contractual obligations.
• Serve as the primary liaison between project teams, business stakeholders, technology teams, and external suppliers.
• Prepare and deliver project status reports, executive updates, and presentations for governance and steering meetings.
• Translate complex technical concepts into clear business language for executive and non-technical audiences.
• Obtain formal customer acceptance of project deliverables and ensure successful project closure.
• Track and maintain project performance metrics to support continuous improvement in delivery quality, demand management, and operational effectiveness.
• Lead, organize, and motivate cross-functional matrix teams comprised of internal resources, application experts, and third-party suppliers.

Senior Project Manager, Data & AI

• Responsible for the technical delivery both as a project manager and site lead for mission critical commissioning projects with minimal supervision while completing assignments that require independent judgement and evaluation.
• Maintain effective communication with clients, contractors and other project team members.
• Develop and maintain client relationships.
• Manage project specific commissioning plans, commissioning procedures, checklists, test scripts, and schedules for Level 1 through Level 5 commissioning activities.
• Lead onsite teams to perform functional performance tests on mechanical, plumbing, and electrical systems.
• Provide project management and coordination to meet client expectations for technical excellence, budget and schedule.

Data Center Commissioning Project Manager

• Lead advanced machine learning model development, continuous performance monitoring, and ongoing maintenance.
• Oversee model governance and ensure full alignment with internal risk frameworks.
• Serve as the primary lead for handling all related internal audit and OCC regulatory requests.
• Develop business strategies that will drive growth, profitability, and competitive success for Capital One in the face of shifting consumer and regulatory demands.
• May manage and develop 1-2 analysts.
• Develop and implement new product and pricing strategies for various lending products; lead product level modeling/analytics.
• Lead direct-to-consumer marketing efforts for select products, and strategic intent for products distributed through the retail channel.
• Drive step-change improvements in credit performance by connecting drivers of future consumer credit trends to historical behavior, creating risk models, and testing hypotheses using rigorous monitoring and analysis.
• Manage and sequence delivery of business intent, build business requirements and execute against the product strategy.

Business Manager – Modeling and Advanced Data Insights

• 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

• Lead specific compensation data products and manage their performance and development
• Set and communicate product strategy aligned with business goals and client needs
• Improve existing products and help develop and launch new offerings
• Analyze survey results and turn findings into clear insights and client-facing stories
• Recommend product changes, priorities, and pricing to leadership
• Work with internal teams and clients to deliver effective, high-quality solutions on time

Compensation Data Product Manager

• Define and articulate the product vision, strategy, and roadmap for enterprise data platforms in alignment with business goals and technological advancements.
• Lead cross-functional teams through the entire product lifecycle, from concept to launch and beyond, for data platform solutions.
• Conduct market research, competitive analysis, and stakeholder interviews to gather insights and inform product decisions related to data management.
• Prioritize features and initiatives based on stakeholder feedback, business impact, and technical feasibility, making trade-off decisions when needed.
• Drive product development efforts, including defining requirements, managing backlog, and ensuring timely delivery of high-quality data platform releases.
• Collaborate with stakeholders across the organization to ensure alignment and drive consensus on key decisions related to data management and governance.
• Continuously monitor data platform performance, analyze metrics, and iterate on features to optimize user experience and business outcomes.
• Connect with internal customers to regularly understand their data needs and build long-lasting relationships.

Senior Product Manager – Data Products

• Possess knowledge of business concepts, tools, and processes that are needed for making sound decisions in the context of the company's business; ability to apply this knowledge appropriately to various situations.
• Oversee the acquisition and consumption of data from structured and unstructured sources, while ensuring quality and comprehensiveness of data for use in analyzing business activities, detecting patterns, and communicating trends.
• Demonstrate an ability to utilize various methods and techniques, including AI, to frame opportunities and conduct analyses that result in productive decisions.
• Develop predictive data models, quantitative analyses, and implement semantic data capabilities utilizing machine learning techniques.
• Lead data exploration and analytics projects and provide on-going coaching regarding visualizations, data mining, and analytic techniques.
• Demonstrate an ability to tell a story with data and create compelling ways to use data to drive actions.

Workforce Insights Specialist – Data Science

• Lead and develop a team of data professionals, providing coaching, mentoring, and training to ensure high-quality project delivery and client satisfaction
• Oversee the processing and management of client pension data, including recurring data feeds and pension payroll file transmissions
• Direct data conversion activities for new client implementations and special projects, ensuring accurate data migration, validation, and integration
• Manage the delivery of annual actuarial valuation extracts, ad hoc reporting requests, data updates, and other client-specific processing needs
• Establish, maintain, and enforce data governance standards while identifying and implementing process improvements and system enhancements

Retirement Administration Data Manager – Defined Benefit

• 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

• Manage strategic relationships with public power partners
• Identify growth opportunities in competitive retail markets and bilateral utility arrangements
• Originate and advance data center infrastructure opportunities with key customers and support customer-facing initiatives
• Participate in the development and delivery of customer proposal presentations
• Coordinate large load registrations, energy management optimization, participate in demand response programs, and develop risk reduction strategies with Structured Trading and Market Operations
• Manage private use networks (PUN) in ERCOT, owning QSE relationships, ensure compliance, and collaborate across teams to optimize energy use for data centers
• Stay up to date on energy regulations, advise on compliance across markets, and build relationships with utilities and regulators in coordination with internal teams
• Support the structuring and execution of retail supply agreements and long-term contracts
• Work with the broader team to prepare internal materials for approvals

Senior Manager, Data Center Infrastructure Origination

Senior Manager, Data Center Infra Origination

• Lead HV, MV, and overall electrical commissioning across all five commissioning phases on multiple concurrent data center sites.
• Act as the owner's electrical commissioning authority for general contractors, designers, and vendors.
• Own the testing and verification program: develop and review it, then drive execution across generators, switchgear, UPS, transformers, ATS/STS, PDUs, and EPMS until every system meets design intent.
• Run on-site inspections, enforce safety, track progress, and resolve issues in the field.
• Lead the final operational handover for electrical, signing off that systems are ready for service.

Commissioning Site Electrical Lead, Data Centers

• Leading and collaborating with software engineers, data engineers, and investment professionals to build innovative AI-based tools using structured and alternate data sources.
• Designing and implementing complex reasoning loops using frameworks like LangGraph, LangChain, or AgentCore, transforming static LLMs into dynamic, goal-oriented agents.
• Developing robust evaluation frameworks and "gold-standard" datasets to measure the performance, faithfulness, and accuracy of generative outputs.
• Scaling AI initiatives and agentic development across Invesco Technology teams by creating reusable patterns, prompt templates, agentic harnesses, skills, and subagents with GitHub Copilot and Claude Code.
• Collaborating with full stack engineers to integrate AI models into business workflows, using AI-assisted coding to move from a notebook experiment to a functional microservice in record time.
• Implementing systematic testing (e.g., RAG evaluation, stress testing) to ensure AI solutions meet the high compliance and reliability standards of the financial services industry.
• Applying emerging techniques in prompt engineering, fine-tuning, and multi-agent systems to solve unique business challenges.

Principal Data Scientist

• 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

• Own the data center mechanical category: CDUs, chillers, pumps, dry coolers, and piping packages for liquid-cooled builds.
• Negotiate supply agreements with mechanical OEMs covering price, lead time, and factory capacity across a multi-year pipeline.
• Dual-source CDU and chiller platforms and drive the qualification work that makes the second source usable.
• Coordinate with manufacturing and design so equipment specs freeze early enough to buy at the lead times the market gives.

Global Sourcing Manager, Mechanical

• 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.

• Manage project deliverables, including developing scope of work and scheduling project reports
• Manage the development of drawings for clients and property/facility management team
• Proactively manage project-related issues as necessary
• Ensure success in initiation, planning, execution, and completion of all projects against agreed upon targets
• Maintain high qualitative and quantitative standards for work performance
• Prepare agendas and meeting materials, lead meetings, and develop and maintain master project budgets and timelines
• Advise and obtain necessary approvals from management of potential organizational changes
• Coordinate and track all vendor RFQ’s and RFP’s
• Review all change orders and other invoices associated with the project

Project Manager, Project & Development Services – Data Center

• 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 Scientist jobs in Texas

See all jobs on JobTailor

Senior AI Data Scientist

Senior Project Manager, Data & AI

Data Center Commissioning Project Manager

Business Manager – Modeling and Advanced Data Insights

Lead Data Scientist – Gen AI Lead

Compensation Data Product Manager

Senior Product Manager – Data Products

Workforce Insights Specialist – Data Science

Retirement Administration Data Manager – Defined Benefit

Data Science Internship

Data Science Intern

Senior Manager, Data Center Infrastructure Origination

Senior Manager, Data Center Infra Origination

Commissioning Site Electrical Lead, Data Centers

Principal Data Scientist

Data Scientist

Global Sourcing Manager, Mechanical

Data Scientist

Project Manager, Project & Development Services – Data Center

Data Programs Manager