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

• 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

• Manage multiple projects on a campus(es) and maintain updated budgets, schedules, and status reports for each
• Create and communicate updates on development program & project status on a monthly basis suitable for executive level reviews.
• Effectively present information in a manner to support efficient decision making
• Work with QTS stakeholders, design, and construction teams to create a master development program for site(s), including a complete campus design solution and capital budget.
• Manage entitlement and permitting needs for each assigned site project(s)
• Implement and manage multi-phased site development plans to achieve time, budget, and quality standards in a predictable fashion.
• Continuously update a campus master plan to provide predictable statistics in a dynamic environment
• Write scopes of work for design, construction, commissioning services & participate in procurement and project cost estimates
• Evaluate and level pricing proposals for design, construction, and commissioning services
• Work closely with strategic procurement team on equipment procurement and delivery process
• Ensure appropriate submittals are coordinated with site stakeholders
• Monitor & create project budget / cost-to-date against overall project budget.
• Establish project schedules and manage teams to on-time completion
• Review and approve monthly pay applications from the contractors
• Review change order requests from contractors and negotiate pricing
• Establish site construction security procedures in conjunction with site security team
• Develop plans for product deployment and review / communicate plans with QTS staff involved
• Collaborate with Sales Engineers and Product teams to aid in custom deal solutioning for prospective clients within the applicable schedule and budget for an assigned location.
• Establish and maintain relationships serving as liaison with key QTS stakeholders
• Represent QTS Interests as leader in OAC meetings
• Create & build relationships that enhance QTS’s ability to be a leader in creating the World’s Most Valuable Data Center Real Estate
• Aid in due diligence efforts for potential new sites on an as-needed basis
• Work with the internal development team to enhance project management processes and protocols

Data Center Construction Project Manager

• Manage multiple projects on a campus(es) and maintain updated budgets, schedules, and status reports for each
• Create and communicate updates on development program & project status on a monthly basis suitable for executive level reviews.
• Effectively present information in a manner to support efficient decision making
• Work with QTS stakeholders, design, and construction teams to create a master development program for site(s), including a complete campus design solution and capital budget.
• Manage entitlement and permitting needs for each assigned site project(s)
• Implement and manage multi-phased site development plans to achieve time, budget, and quality standards in a predictable fashion.
• Continuously update a campus master plan to provide predictable statistics in a dynamic environment
• Write scopes of work for design, construction, commissioning services & participate in procurement and project cost estimates
• Evaluate and level pricing proposals for design, construction, and commissioning services
• Work closely with strategic procurement team on equipment procurement and delivery process
• Ensure appropriate submittals are coordinated with site stakeholders
• Monitor & create project budget/cost-to-date against overall project budget.
• Establish project schedules and manage teams to on-time completion
• Review and approve monthly pay applications from the contractors
• Review change order requests from contractors and negotiate pricing
• Establish site construction security procedures in conjunction with site security team
• Develop plans for product deployment and review/communicate plans with QTS staff involved
• Collaborate with Sales Engineers and Product teams to aid in custom deal solutioning for prospective clients within the applicable schedule and budget for an assigned location.
• Establish and maintain relationships serving as liaison with key QTS stakeholders
• Represent QTS interests as leader in OAC meetings
• Create & build relationships that enhance QTS's ability to be a leader in creating the World's Most Valuable Data Center Real Estate
• Aid in due diligence efforts for potential new sites on an as-needed basis
• Work with the internal development team to enhance project management processes and protocols

Data Center Construction Regional/Program Manager

• Oversee operational processes to ensure correct inventory levels are maintained and orders are completed accurately and on time
• Review workload and assign tasks to employees
• Properly train and coach the warehouse team and provide positive developmental opportunities; recommend performance improvement actions as needed
• Correctly utilize warehouse management system and maintain appropriate work documents
• Establish, maintain and promote exceptional customer service
• Correctly interpret and enforce company policies and safety procedures to ensure compliance
• Safely operate various equipment and tools
• Provide support and backup to warehouse management
• Track orders and investigate problems
• Catalog and track goods and/or supplies
• Adhere to the 7S program by maintaining a clean environment
• Work in a safe manner that protects you and your team members

Data Center Lead – Afternoon 2nd Shift

Data Center Lead – Night Shift

• 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

• Providing advanced analytics, ML model design, technical leadership.
• Collecting, analyzing and interpreting large data sets to identify trends, patterns, and provide key business insights.
• Performs data mining, cleaning, and aggregation processes to prepare data, implement data models, conduct analysis, and develop databases.
• Develops insights and reports from multiple structured and unstructured data sources using programming, statistical, and analytical techniques and tools.
• Maintains continuous collaboration with teams to understand the underlying purpose, focus, and objective of each data analysis project to ensure alignment and support.
• Designs, develops, and implements the most valuable data-driven solutions for the organization.
• Works autonomously, but may provide a leadership role for the work group through knowledge in the area of specialization.

Data Science Lead

Data Center Lead – Weekend 3rd Shift

Data Center Lead, Weekend Afternoon, 2nd Shift

Data Center Lead – Weekend, Afternoon, Night Shifts

Data Center Lead – Day – 1st Shift

• Manage data science solutions from end to end, including business problem definition, data exploration, model development, insight generation, and presentation to senior leadership.
• Develop forecasts to project member eligibility, program volumes, and operational capacity needs.
• Identify and evaluate leading indicators that signal future performance, risks, or opportunities.
• Assist in developing benchmarks, targets, and goals to support program planning and performance management.
• Measure program effectiveness and quantify business impact.
• Create segmentation models to support targeted outreach, intervention planning, and member-level prioritization.
• Build and deploy machine learning models in a cloud-based environment using tools such as Python, PySpark, and SQL.
• Model care gap closure opportunities and assess potential impact on HEDIS Stars measures.
• Translate complex data, modeling approaches, and analytic findings into clear insights for non-technical leaders and stakeholders.
• Collaborate with business partners, data science peers, technology teams, and operational stakeholders to deliver scalable analytic solutions.

Lead Data Scientist

• Develops, implements, and provides production support of business intelligence reporting and sophisticated analytical model development
• Develops architecture, data availability, and data model support
• Creates scalable, efficient, and automated processes for large scale data analyses for model development, validation, and implementation
• Organize user interfaces and data visualization tools to make data analyses more effective and accessible
• Trains users to transform data into action-oriented information and to use that information to make critical business decisions
• Explores available data and discover patterns, anomalies and trends
• Develops descriptive, predictive and/or prescriptive statistical models to address business problems
• Works with large data sets in a hybrid cloud, using machine learning (ML) and artificial intelligence (AI) methods to help define requirements and set expectations
• Other duties as assigned

Business Data Scientist – Senior

• responsible for the engineering work necessary for successful creation, deployment and managing of AI capabilities of the Intelligent Delivery Platform
• ensuring data quality
• creation of new data pipelines
• optimization and management of existing data pipelines
• ingestion and curation of data sources for Gen AI purposes (including chunking/embedding strategies for RAG system)
• AI Agent delivery
• Prompt Engineering
• selection and configuration of AI-specific tools and platforms
• management and monitoring of AI models through MLOps tools and model ops practices
• operationalizing AI capabilities, working closely with larger team who will supplement where traditional application development support is needed

Lead Data Science Engineer

• Serve as the primary point of contact for At Work-related data and analytics needs
• Partner with CAPTRUST’s centralized data team to prioritize, design, and improve data solutions supporting At Work
• Help establish consistent definitions, metrics, and reporting standards across the At Work practice
• Improve data quality, clarity, and usability over time
• Support and enhance internal and client-facing reporting used by At Work teams
• Work closely with Operations to understand recurring reporting needs and reduce one-off or manual efforts
• Develop dashboards and reports that support operational planning, advisor effectiveness, and leadership decision-making
• Translate reporting outputs into insights that inform action, not just describe activity
• Develop qualitative and quantitative measures of client and participant engagement, trust, and relationship health
• Help establish ongoing feedback loops across the client and participant lifecycle, beyond episodic surveys
• Identify trends that signal strengthening relationships, stagnation, or potential breakdowns
• Support analysis related to the annual financial wellness survey and other experience-related initiatives
• Analyze patterns associated with strong long-term outcomes such as sustained engagement, retention, and expansion of advisory relationships as needs evolve
• Partner with leadership and Operations to identify where additional investment of time or resources may be needed
• Help reduce reliance on anecdotal feedback through clearer, shared insight

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