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

Development Project Manager – TFO Data Center Construction

• Leads the strategy, design, and governance of enterprise data architecture to enable scalable, secure, and high-quality data foundations across the organization.
• Owns the definition and evolution of data architecture standards, information models, and data platform integration patterns that underpin analytics, AI, and operational systems.
• Translates business and technology priorities into cohesive, AI-ready data architecture strategies.
• Ensures alignment across data engineering, analytics, AI/ML, and enterprise platforms,
• Establishes a modern, governed, and interoperable data ecosystem that supports enterprise-scale data, AI, and digital transformation initiatives.

Senior Manager, Data and Information Architecture

• From leading multi-functional projects to building modern, data-driven tools, this job is all about creating momentum.
• One part of the day may involve designing a Power BI dashboard or automating a key process; another may involve aligning leaders across functions, breaking down silos, and driving initiatives that improve efficiency, visibility, and overall performance.
• Our team doesn’t just support the business—it helps shape it.
• By influencing leaders, introducing new ways of working, and delivering solutions that create real results, this person becomes a key driver of change across the organization.
• This role offers the opportunity to shape data-driven strategies that directly impact product performance and customer satisfaction.
• You will work in a collaborative environment with innovative tools and technologies, while influencing key decisions at a leadership level and leading key quality projects.
• Advanced analytics & forecasting Develop and refine statistical models to forecast trends and identify quality risk points.
• Perform complex analyses to solve problems and guide strategic actions.
• Deliver insights through compelling storytelling and actionable recommendations.
• Data Management & Architecture Identify, collect, clean, and prepare relevant data to meet complex or multi-functional needs.
• Supervise data pipelines, gathering, architecture, and accessibility.
• Ensure operational service guarantees.
• Quality Systems & Governance Manage trending audit results and follow-up actions for operational guarantees.
• Track and communicate process, method, and product changes.
• Ensure compliance with data governance standards, including security, integrity, and confidentiality.
• Collaboration & Leadership Act as liaison with analysts and assistance in quality data capture and surveillance.
• Support or lead market action coordination with Product Manager.
• Serve as a member of the Product Performance Leadership Team.
• Train and mentor junior analysts and assist field employees in developing data analysis skills.
• Continuous Improvement Share standard methodologies internally and externally.
• Identify and implement new methods and technologies to enhance data analysis capabilities.
• Automation & Visualization Create scripts and tools to automate repetitive tasks and optimize response times.
• Design dashboards and reports using Power BI and Databricks for critical metric visibility.
• Basic Programming Develop coding in DAX, SQL, and Python.

Senior Quality Data Support Manager

• responsible for collecting data and using wide range of data science techniques, including but not limited to data wrangling, profiling and visualization, statistical inference, to uncover actionable insights or build analytics solutions that guide decision making and strategic planning
• works autonomously within a specialized business management function and may provide work direction to others
• provides seasoned specialized knowledge, advice and/or guidance to various stakeholders and team members
• focuses on short to medium - term issues (e.g. 6-12 months)
• undertakes and completes a variety of complex projects and initiatives requiring specialist knowledge and/or the integration of cross functional processes within own area of expertise

Data Scientist II – FCRM – Screening Capabilities

• Provide technical leadership across the Analytics function
• Create, develop, and maintain AML typologies
• Collaborate with cross-functional teams and support Financial Intelligence Units (FIU)
• Oversee the execution of multiple projects
• Ensure successful project completion within established timelines

Data Scientist – FCRM

• Lead the design, development, and deployment of advanced statistical, machine learning, and AI solutions—including LLM-powered applications—to solve complex business, workforce, and organizational challenges.
• Translate ambiguous business and HR questions into well-defined analytical approaches, scalable data products, and decision-support tools.
• Design and oversee end-to-end data science workflows, including data extraction (e.g., enterprise data warehouses), validation, modeling, deployment, and performance monitoring.
• Integrate data from multiple internal and external sources to create modeling-ready datasets, reusable data assets, semantic layers, and metadata frameworks that enable scalable and self-service analytics.
• Develop and productionize predictive and prescriptive models to explain outcomes, forecast behavior, and identify risks and opportunities.
• Build and deploy advanced AI solutions using modern frameworks (e.g., LLMs, embeddings, RAG architectures), and lead experimentation and rapid prototyping to evaluate emerging capabilities.
• Embed analytics and AI solutions into business processes through automation, system integration, and near real-time data capabilities.
• Partner with HR Business Partners, talent leaders, executives, data engineering, and IT teams to deliver actionable insights and ensure alignment with architectural, security, and data quality standards.
• Provide technical leadership across data science initiatives, ensuring consistency with best practices, methodologies, and quality standards.
• Communicate complex analytical insights and AI concepts clearly to non-technical stakeholders, influencing strategic and operational decision-making.
• Mentor and coach junior team members, elevating team capabilities in AI, machine learning, and analytics best practices.
• Ensure adherence to responsible AI principles, including data privacy, bias mitigation, security, and ethical use of employee data.
• Stay current on emerging AI and analytics trends, proactively identifying opportunities to incorporate new technologies into enterprise use cases.

Senior Data Scientist – AI, People Analytics

• Partner with Marketing to Define and Solve Problems – Work closely with marketing stakeholders to understand business challenges, define success metrics, and translate needs into analytical approaches that drive performance across campaigns and channels.
• Design and Deliver Data-Driven Solutions – Apply statistical analysis and machine learning to develop solutions that address business needs, then present findings, influence decisions, and gain alignment on adoption.
• Lead Experimentation and Optimization – Develop and manage testing frameworks (A/B testing, campaign experimentation) across channels and markets. Analyze results and provide clear recommendations to improve performance and inform future strategy.
• Translate Results into Business Impact – Clearly communicate insights and quantify outcomes (e.g., campaign performance lift, engagement improvements, ROI) to ensure stakeholders understand the value and take action.
• Partner to Operationalize Solutions – Collaborate with Technology and Engineering teams to transition validated models into production, supporting implementation through scalable pipelines and processes.
• Influence Through Storytelling – Present insights and recommendations to both technical and non-technical audiences, including senior stakeholders, to drive alignment and decision-making.

Senior Data Scientist – Marketing Analytics

• Lead a team of business data analysts responsible for implementation, enhancement, and maintenance of AML Transaction Monitoring platform
• Bring strong domain expertise in Securities Compliance and understand transaction patterns in trading
• Collaborate with Technology, Data, and Modeling teams for end-to-end delivery
• Ensure engagement with Audit and Compliance stakeholders to support issue validation

AML Business Data Manager

• Collect data and use data science techniques to uncover insights
• Provide oversight and consultative advice as the lead Data Scientist
• Evaluate technical solutions and lead innovation to solve complex business issues
• Provide strategic and day-to-day direction on CTR program activities
• Coordinate with internal and external stakeholders for audits and examinations

Lead Data Scientist

• 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

Data & Analytics Lead

• Lead the analytics center of excellence for Gainsight's GTM organization, with an initial focus on Sales and Customer Success
• Set standards for dashboard design, metric definitions, data governance, and insight delivery across the team
• Own the quality and trust of all GTM reporting, ensuring leadership can rely on the numbers without second-guessing them
• Act as a mentor to peer analysts, focused on technical and business acumen, escalation support, knowledge and skills sharing
• Own end-to-end analytics across bookings, pipeline health, forecasting, GRR, NRR, renewals, and customer expansion
• Partner with the GTM Planning team on evolution of planning models that support AOP, quota setting, capacity planning, and scenario analysis
• Deliver executive-ready dashboards and weekly/monthly/quarterly operating cadences for Sales and CS leadership
• Partner with Finance on bookings-to-revenue reconciliation and board-level reporting
• Proactively surface risks and opportunities, moving from answering questions to anticipating them
• Lead the transformation from static BI dashboards to AI-enabled, self-service data exploration for GTM stakeholders
• Partner with the GTM Data Architect to establish the semantic layer — the business-side definitions of ACV, GRR, pipeline, and churn that enable reliable AI querying
• Design and deploy AI-powered analytical workflows including natural language querying, anomaly detection, and proactive insight surfacing
• Enable Sales and CS leaders to query data independently without routing every question through the analytics team
• Stay current on the evolving landscape of AI analytics tooling and bring forward recommendations
• Serve as a trusted analytical thought partner to Sales VPs, CS leadership, and RevOps
• Translate complex data into clear business recommendations, connecting the numbers to the "so what"
• Support strategic planning processes including territory design, AOP, and Rules of Engagement

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