Data Scientist

• Manage the day-to-day execution of multiple data science and machine learning projects.
• Translate business problems and strategic priorities into project scopes, objectives, milestones, deliverables, and success criteria.
• Maintain project plans, backlogs, roadmaps, timelines, dependencies, risks, decisions, and action items.
• Coordinate work across data scientists, data engineers, software engineers, ML engineers, product managers, and business stakeholders.
• Facilitate sprint planning, standups, retrospectives, status reviews, demos, and project working sessions.
• Identify blockers, drive resolution, and escalate decisions when necessary.
• Ensure project documentation, requirements, assumptions, and decisions are current and accessible.
• Provide regular reporting on progress, risks, dependencies, and expected outcomes.
• Track requirements for reproducibility, versioning, testing, deployment, monitoring, and documentation.
• Coordinate model release readiness, production handoffs, and post-deployment follow-up.
• Ensure teams consider data quality, model performance, drift, reliability, security, and support ownership.
• Help establish processes for model promotion, retraining, monitoring, incident response, and model retirement.
• Create scalable operating processes, templates, dashboards, meeting cadences, and documentation standards for the Data Science organization.
• Identify recurring delivery issues and recommend improvements to processes, tools, roles, or decision-making.

Data Science Project Manager

• Support the Annual Heart Disease and Stroke Statistical Update
• Extract, analyze, and summarize prevalence, mortality, healthcare utilization, expenditure, and outcome data using national datasets such as NHANES, NHIS, CDC WONDER, HCUP, and MEPS
• Assist with collection, management, analysis, and reporting of cardiovascular disease and stroke-related data
• Create and update statistical tables, figures, charts, and supporting documentation for scientific reports and publications
• Develop and maintain standard operating procedures, analytic documentation, and process guides for data extraction, analysis, reporting, and quality assurance
• Collaborate with epidemiologists, data scientists, and scientific volunteers to respond to data requests and support annual publication activities

Intern, Epidemiology, Data Science – Evaluation

• Assist with preparing, cleaning, validating, and documenting clinical, registry, and research datasets
• Conduct descriptive and inferential statistical analyses under senior team guidance
• Support study design, sample size and power considerations, statistical analysis plans, and interpretation of results
• Develop and evaluate statistical models, including regression, survival analysis, longitudinal analysis, and mixed-effects models
• Create reproducible analytical workflows using R, Python, SAS, or other approved statistical tools
• Perform quality-control reviews of data, code, tables, figures, and analytical outputs
• Produce tables, figures, data visualizations, and summaries for scientific and business audiences
• Contribute to literature reviews, manuscripts, abstracts, conference materials, and presentations
• Participate in team meetings, code reviews, documentation activities, and research best practices
• Collaborate with biostatisticians, data scientists, clinicians, and research partners to support study design, analysis, interpretation, and scientific communication

Intern, Data Science, Biostatistics

• Support the design and development of LLM-powered applications and agentic AI workflows for clinical, biomedical, and operational research use cases
• Apply LLMs to modeling and analytical tasks, including information extraction, classification, summarization, question answering, and workflow orchestration
• Experiment with prompt design, structured outputs, retrieval-augmented generation, embeddings, vector search, tool use, and multi-step agent workflows
• Prepare, clean, organize, and document data used in LLM and generative AI experiments
• Develop reproducible prototypes and workflows using Python and approved AI/ML tools and platforms
• Design and perform evaluations of LLM systems using quantitative and qualitative measures
• Conduct validation, error analysis, robustness testing, and comparison of model or workflow alternatives
• Assess hallucination, factual consistency, relevance, reliability, bias, privacy, and reproducibility
• Document methods, assumptions, prompts, evaluation results, limitations, and recommended improvements
• Contribute to technical documentation, presentations, abstracts, manuscripts, and cross-functional project discussions

Intern, Data Science, Machine Learning, AI

• Drive Data Quality performance and KPI compliance across North America
• Monitor Data Quality KPIs and analyze performance trends
• Identify root causes of Data Quality gaps
• Provide actionable insights and recommendations to branch and regional leadership
• Ensure follow-up and accountability on KPI performance across North America
• Act as subject matter expert on Data Quality processes and data compliance
• Support branches in resolving Data Quality issues through structured follow-up
• Identify recurring error patterns and implement corrective actions
• Promote adherence to TMS usage standards and best practices
• Deliver onsite and remote Data Quality and KPI training sessions across North America
• Provide hands-on support to managers and operational teams
• Identify training needs and develop targeted training plans
• Maintain and update training materials and user guides
• Utilize Power BI, DQA, and other tools to monitor Data Quality performance
• Support development and maintenance of KPI dashboards and reports
• Ensure consistency and accuracy of Data Quality reporting
• Enable operations teams to interpret and use performance data
• Identify and lead initiatives to improve Data Quality and operational efficiency
• Collaborate with operational staff and global stakeholders on improvement initiatives
• Support implementation of new tools, processes, and global programs
• Contribute to strengthening Data Quality culture across operations

Business Change Manager, Data Quality

• Develop, train, and deploy production-grade predictive and prescriptive machine learning models
• Architect, fine-tune, and evaluate enterprise Generative AI systems, including RAG pipelines, custom LLM applications, and prompt engineering frameworks
• Design and deploy autonomous AI agents and multi-agent workflows
• Build advanced analytics models to measure campaign performance, predict customer behavior, and maximize ROI
• Create executive-ready presentations and dashboards communicating algorithmic outcomes, metrics, business value, and ROI
• Analyze raw client data and build optimized analytics datasets in cloud environments
• Lead client workshops to identify business objectives, map data landscapes, and translate business problems into data science methodologies
• Create solution and design documentation for client data science architectures and ML pipelines
• Work independently and across large teams on multiple client engagements
• Crosstrain junior Data Scientists/Analysts and provide technical leadership and code reviews
• Develop skills through on-the-job and formal learning to stay current with AI/ML trends
• Assist in pre-sales by scoping client opportunities and estimating work and effort

Senior Consultant, Data Science & AI

• Lead and provide day-to-day direction to small crews of Data Technicians on active commercial construction sites
• Assist the Foreman with coordinating daily work assignments, manpower, installation priorities, and project workflow
• Pull, route, dress, terminate, test, troubleshoot, and label CAT5e, CAT6, CAT6A, and fiber-optic cabling
• Install and maintain cable support systems, pathways, J-hooks, ladder rack, sleeves, and other structured cabling infrastructure
• Install and maintain low-voltage devices and equipment, including WAPs, speakers, projectors, displays, card readers, access-control devices, electric strikes, locks, crash bars, transmitters, receivers, and DAS equipment
• Read and interpret construction drawings, floor plans, reflected ceiling plans, riser diagrams, specifications, and installation details
• Lay out work for technicians and ensure installations meet drawings, specifications, customer requirements, and FSG standards
• Monitor crew productivity and identify issues affecting schedule, quality, or project completion
• Perform quality-control inspections of cabling, terminations, labeling, pathways, device installations, and completed work
• Verify testing results and troubleshoot failed cables, connectivity issues, damaged infrastructure, or installation deficiencies
• Train, mentor, and develop junior technicians while reinforcing proper installation methods and industry best practices
• Serve as a technical resource for troubleshooting installations and interpreting project requirements
• Coordinate field activities with the Foreman, Project Manager, General Contractor, other trades, and customer representatives
• Identify material, equipment, and tool requirements; assist with receiving, staging, organizing, tracking, and maintaining project materials and equipment
• Maintain cable identification, labeling, testing documentation, punch lists, and project closeout information
• Identify field conflicts and communicate potential problems to project leadership
• Participate in walkthroughs, inspections, punch-list completion, testing, commissioning, and turnover activities
• Attend required safety meetings and enforce FSG and customer safety policies among assigned crew members
• Ensure safe and correct use of PPE, tools, ladders, lifts, and equipment
• Maintain a clean, organized, professional, and safe work environment
• Assist other crews or project teams as necessary to meet project schedules and customer commitments
• Perform hands-on installation work while maintaining responsibility for assigned work quality and productivity
• Communicate daily progress, manpower needs, material shortages, installation challenges, and schedule impacts to field leadership
• Perform additional project-related duties and leadership responsibilities as assigned

Data Scientist jobs in Texas