Data Analyst

• Analyze large and complex datasets to identify trends, risks, opportunities, and root causes impacting business performance
• Develop and maintain Power BI dashboards, reports, and visualizations that enable data-driven decision-making across the organization
• Partner with stakeholders to gather requirements, define business needs, and translate those needs into scalable analytics solutions
• Serve as a bridge between business and technical teams, ensuring alignment on requirements, capabilities, and project objectives
• Build data models, predictive analytics, and forecasting tools to improve planning and operational effectiveness
• Write and optimize SQL queries and leverage Python or other analytical tools to automate reporting and perform advanced analyses
• Support inventory optimization, fill-rate performance, supply-demand balancing, and forecasting initiatives
• Present findings and recommendations to audiences ranging from operational teams to senior leadership
• Lead and contribute to cross-functional projects focused on process improvement, business intelligence, and operational excellence

Aftermarket Business Data Analyst

• Own Foley's enterprise data model
• Drive the medallion architecture from a product definition perspective
• Own Silver and Gold layer data definitions
• Prioritize the engineering backlog in partnership with the VP of Engineering
• Be the primary data platform partner for business stakeholders
• Own stakeholder communication
• Maintain a weekly touchpoint with the AI Value Creation Office
• Own delivery against quarterly KRs
• Own the product roadmap for Foley's intelligence self-service platform
• Own the API layer as a product
• Define and maintain the metric layer
• Partner with the data analyst and engineering to enable self-service intelligence
• Drive platform adoption and capability enablement across the organization
• Own the capabilities and paved paths backlog

Staff Product Manager, Data & Analytics

• Working in a fast-paced, innovative, and change-oriented work environment
• Using programming skills to explore, examine and interpret large-scale data in various forms
• Determine the appropriate techniques to manipulate complex high-volume data, develop insights through analysis and modelling, evaluate business problems, and improve our analytical speed-to-insight
• Perform data mining and analyzing of structured and unstructured data associated with claims, policy, payment activities to solve complex business problems using advanced techniques and leveraging industry cutting-edge technology
• Focus on automation and utilizing technology to provide repeatable reporting solutions to promote self-service culture for business partners
• Building a strong network of peers and mentors
• Attending on-site technical and professional development classes
• Presenting accomplishments to leadership across the organization
• Participating in sponsored community service events

Data Analytics Co-Op

• Translate complex, multi-source datasets into concise executive narratives that communicate not just findings but implications and data limitations.
• Develop and maintain analytical deliverables including executive-facing presentations, insight memos, and self-service dashboards.
• Write sophisticated queries against Palantir Foundry Ontology to extract, transform, and validate data from core operational tables and dbt models.
• Contribute to the analytics engineering layer that underpins your work: extend dbt models where needed, help stand up new data pipelines.
• Partner with senior stakeholders, including the Chief Strategy Officer, Head of Revenue, and other executive leads to understand their data questions.
• Uphold data modeling best practices in the work you touch: clear documentation, version control via Git, incremental build strategies, and data quality validation.
• Identify gaps and inconsistencies in data and proactively surface them rather than papering over them.
• Leverage AI tools to accelerate both analytical and engineering work while applying rigorous critical evaluation to any AI-generated output.

Strategic Data Analyst, Growth & Placement

• Own the strategy, design, and continuous improvement of next best action (NBA) and next best offer (NBO) frameworks for existing and former consumer and small business customers.
• Build and manage decisioning logic and prioritization models that balance customer needs with business objectives across all product lines including deposits, lending, wealth, treasury management, and merchant services.
• Identify and operationalize data-driven moments that matter — leveraging behavioral signals, life events, transactional triggers, and engagement patterns to ensure the right message is communicated to the right customer at the right time through the right channel, capitalizing on the highest-value opportunities to drive meaningful engagement and action.
• Develop and maintain always-on audience segmentation strategies that identify the right customers for the right marketing or sales action at the right time.
• Leverage existing and former customer data environments to surface high-value opportunities for cross-sell, reacquisition, engagement deepening, and retention.
• Own the end-to-end process of building, managing, and delivering targeted customer audiences for activation across all marketing and sales channels including direct mail, email, targeted digital advertising, and outbound calling.
• Manage data pipelines and workflows required to extract, transform, and deliver audience files and segments to channel execution partners and platforms in a timely and accurate manner.
• Ensure audiences are refreshed and maintained on an always-on cadence to support continuous marketing and sales motions rather than solely episodic campaign activity.
• Partner with channel owners and marketing operations to ensure seamless audience ingestion, suppression logic, and contact frequency governance.
• Own and manage the technology stack and data infrastructure supporting decision intelligence and audience activation, including cloud data environments (preferably Snowflake), CRM platforms, and marketing activation tools.

Senior Marketing Contact Strategy, Analytics Manager

• Lead the design and implementation of data and information architecture
• Sustain & troubleshoot PowerBI dashboards
• Collaborate with Customer Solutions teams
• Investigate reporting issues
• Monitor use of reports and dashboards

Senior Data Analyst, Customer Analytics

• Collect, organize, and maintain sustainability program data from online initiatives and engagement activities.
• Track participation, engagement, and learning outcomes related to sustainability programs for online students.
• Assist with creating surveys, forms, and assessment tools to gather feedback and measure program effectiveness.
• Analyze data and identify trends, opportunities, and areas for improvement.
• Develop dashboards, reports, infographics, and data visualizations that communicate program impact.
• Support the collection and analysis of data for annual sustainability reports and strategic planning initiatives.
• Research sustainability benchmarks, best practices, and emerging trends relevant to higher education and online engagement.
• Collaborate with other Eco Reps to evaluate the effectiveness of campaigns, events, workshops, and educational programs.
• Present findings and recommendations to the Office of Sustainability staff and student teams.
• Maintain accurate records and documentation of sustainability-related metrics and outcomes.
• Assist with measuring participation in sustainability challenges, online learning opportunities, and virtual engagement initiatives.
• Support data-informed decision-making by providing actionable insights and recommendations.
• Monitor engagement metrics for online sustainability programming, newsletters, social media campaigns, webinars, and virtual events.
• Analyze participation patterns among online students to identify opportunities for increased engagement.
• Evaluate the effectiveness of virtual sustainability education initiatives and recommend improvements.
• Assist in developing metrics that capture the impact of sustainability programs on online learners.
• Support virtual focus groups, surveys, and feedback collection efforts.
• Compile monthly and semester impact reports.
• Track sustainability engagement goals and key performance indicators (KPIs).
• Assist with data collection for STARS reporting and other institutional sustainability assessments.
• Create visual summaries and presentations that communicate results to campus stakeholders.
• Support the development of data-driven recommendations for future sustainability initiatives.

Online Data Analytics Eco Representative

• Work directly with Marketing, Sales, and CX leaders to diagnose business challenges, define analytical roadmaps, and drive growth strategies.
• Develop rigorous analyses, models, and frameworks to optimize customer acquisition, lifecycle engagement, and retention.
• Build scalable machine learning solutions (e.g., targeting, segmentation, uplift modeling, LTV prediction) that improve growth efficiency and ROI.
• Drive acquisition, retention, and monetization through data-driven experimentation and modeling.
• Translate complex data insights into clear, actionable recommendations that influence decision-making at all levels of the organization.
• Collaborate with engineering teams to productionize models and analytics pipelines with high reliability and performance.
• Familiar with state of art AI solutions in Data Science domain and mentor Jr. data scientists.
• Drive best practices in experimentation, measurement, and growth analytics across the company.

Lead Data Scientist – Property Catastrophe Modeling, Geo-Analytics

• Lead the design and implementation of robust data infrastructure to support analytics and business intelligence
• Manage database engineering efforts to optimize data storage and retrieval
• Ensure effective data warehousing solutions that support efficient data management and reporting
• Drive the creation of high-value assets that support strategic decision-making
• Develop and manage customer data platforms to capture and analyze customer behavior and preferences
• Oversee consumer segmentation efforts to identify and target key audience segments
• Lead efforts to identify consumer trends and behaviors to inform product development and marketing strategies
• Develop and refine target audience profiles to enhance marketing effectiveness
• Leverage propensity modelling to predict customer behavior in the purchase funnel and optimize marketing efforts
• Conduct and oversee first-party custom research to gather unique consumer insights
• Translate data into actionable customer insights to drive business growth and customer satisfaction
• Oversee website analytics to optimize online user experience and engagement
• Develop and implement marketing mix models to evaluate and optimize marketing investments
• Utilize predictive analytics to forecast marketing outcomes and inform strategy
• Lead advanced marketing attribution efforts to accurately measure the impact of marketing activities
• Analyze commercial performance data to identify opportunities for growth and improvement
• Define brand equity and strength
• Oversee network analytics to optimize distribution and operational efficiency
• Lead product analytics efforts to inform product development and lifecycle management
• Utilize financial analytics to support budgeting, forecasting, and financial planning.

VP of Analytics, Insights, and Data Products

• Apply engineering principles and analytical techniques to drive continuous improvement in FSA SW deployment process.
• Play an integral part in the FSA SW deployment process by establishing and monitoring timing target levels at each of the milestone phases to validate sw readiness.
• Manage and direct FSAPM Jira activities to ensure robust service timing plans as well and minimize Jira hygiene errors/concerns.
• Function as the leader and subject matter expert for EE&S Global FSAs.
• Coordinate activities and drive improvements to achieve KPIs.
• Remove Barriers: Lead best practices, and the development of solutions for throughput constraints.
• Work cross-functionally with DnR's, Plant Vehicle Teams, Ford Customer Service Division, OTA Operations, and Suppliers.
• Develop relevant KPIs and data visualizations to enable a clear, real-time understanding of actual vs. expected SW quality and process performance.

Field Service Analyst – Time and Data Management

• Develop and execute the analytics strategy for the People Relations & Enablement function
• Define, measure, and monitor key metrics that support enterprise decision-making and risk mitigation
• Design and deliver executive dashboards, scorecards, and reports that provide actionable insights
• Analyze people-related data to identify trends, emerging issues, organizational hotspots, and systemic risks
• Translate complex data into compelling narratives and recommendations for senior leaders and stakeholders
• Provide insight-driven guidance that helps leaders understand root causes and make informed decisions
• Partner with Technology, Workforce Analytics, Compliance, and Legal teams to ensure data integrity, governance, and confidentiality
• Establish data definitions, reporting standards, and governance processes that promote consistency and transparency
• Support automation initiatives and real-time reporting capabilities that enhance operational effectiveness
• Measure the impact of investigations, training initiatives, policy implementation, and resolution strategies
• Identify opportunities for early intervention and prevention by leveraging analytics to reduce recurring issues
• Create feedback loops that inform policy development, training strategies, and continuous improvement efforts
• Advance a proactive, data-informed People Relations & Enablement operating model focused on organizational health and trust.

People Relations & Enablement Analytics, Reporting Manager

• Perform advanced financial analysis and reporting to support strategic decision-making
• Develop and maintain sophisticated financial models for cash forecasting, capital planning, treasury management
• Conduct benchmarking, KPI analysis, and variance reporting to identify trends, risks, and opportunities
• Oversee budgeting processes, cost accounting, and productivity standards; provide recommendations for process improvements
• Mentor accounting staff, provide financial systems training, and support professional development within the finance team
• Present complex financial information and recommendations to senior leadership

Senior Financial Analyst – Cash Accounting, Analytics

• Define and execute the enterprise Data, Analytics, AI, and Automation strategy
• Develop and maintain a multi-year roadmap for data modernization
• Advise executive leadership on emerging technologies, AI trends, opportunities, and risks
• Manage enterprise data platform architecture, including the Enterprise Data Warehouse, Azure Data Lake
• Establish enterprise data governance, data quality, and master data management capabilities
• Develop enterprise analytics capabilities that improve decision-making
• Drive adoption of intelligent automation and AI capabilities to improve productivity
• Build, lead, and develop a high-performing organization

Senior Director, Enterprise Data, Analytics, AI & Automation

• Accelerate the application of value-added analytics and machine learning into the portfolio of products for Manufacturing Analytics.
• Drive analytic excellence into product teams by collaborating with Data Scientists, Data Engineers and Software Engineers in analytic and machine learning methods.
• Work closely with the Product Manager and Product Owner to translate Business Value needs into analytic deliverables and, where appropriate, software products for delivery by product teams.
• Work hands-on with the team and other partners to deliver solutions that meet our customer's requirements and needs.
• Act as a consultant to the business vs. an order taker.
• Balance "doing it right" with "speed to delivery" by identifying and mitigating risk, generating options, educating business and other decision makers, and taking on justified technical debt.

Data Scientist, Manufacturing Analytics

• Review industry literature and research publications and maintain a system to curate publications, competitive intelligence, and internal research/reports.
• Create landscape summaries on topics relevant to higher education and update with new data and publications on an ongoing basis.
• Use third-party platforms to extract and summarize market data on programs and populations.
• Support Product Marketing in providing data summaries for program reviews and investigating new programs or products.
• Conduct deep-dive ad hoc research on market and competitive trends.
• Build, maintain, and update data models of external data sources (e.g., IPEDS), using tools such as Microsoft Fabric/PowerBI.
• Create and maintain data Python data ingestion notebooks in BigQuery and Microsoft Fabric.
• Use existing data models to monitor and summarize internal performance trends across products, segments, and demographics.
• Build and enhance reports and dashboards according to feedback, insights, and institutional goals.
• Actively seek opportunities to improve and anticipate feedback on analytic projects and tools.
• Present analysis findings to diverse audiences in a variety of formats.
• Utilize project management software to keep track of multiple priorities and projects.
• Attendance, punctuality, and reliability are essential functions of this role.

Market Research Data Analyst

• Develop and deploy advanced analytical models to improve our understanding of Network supply and demand, identify operational inefficiencies, and deliver actionable recommendations to leadership.
• Implement real-time dashboards and reporting to track and assess Network performance against established metrics.
• Challenge the status quo and be willing to propose and test new strategies for increasing competition and engagement within our service provider network.
• Analyze feedback, ratings, and reviews from multiple sources and stakeholders to gain insights into service quality, customer satisfaction, and provider satisfaction, identifying actionable insights for improvement.
• Develop operational and performance data to generate actionable insights and recommendations for 3rd party service providers, enabling them to enhance their service delivery, optimize processes, and align more closely with organizational objectives.
• Analyze the capacity of our Network, identifying gaps, weaknesses, and opportunities to improve operational efficiency and service quality, making recommendations for Network recruiting, retention, and optimization.
• Leads test and pilots for process changes as a result of analysis and communicates the results and recommendations to all areas of management.
• Serves as an internal data analytics expert by ensuring consistency in data analysis methodologies and sharing of best practices.

Lead Data Analyst, Contact Center Operations

• Responsible for the generation and analysis of marketing data for the purpose of translating data into information that will be used to demonstrate insight that drives marketing performance and investment decisions.
• Builds and maintains dashboards and reporting frameworks that track marketing performance across marketing programming, including but not limited to pipeline contribution, conversion, and return on investment.
• Analyzes data across multiple systems (Customer Relationship Management or CRM), marketing automation, web analytics, and digital platforms, to identify patterns, trends, opportunities, and risks.
• Translates complex data into clear, concise insights and recommendations that influence marketing strategy and investment decisions.
• Partner with channel strategy and marketing operations to inform prioritization, campaign optimization, and performance tradeoffs.
• Develop and evolve measurement approaches including attribution, funnel analysis, and campaign performance frameworks.
• Ensure data quality, consistency, and alignment of key metrics across systems and stakeholders.
• Support planning and performance reviews (quarterly, annual) with data‑backed insights and recommendations.
• Deliver ad hoc and deep‑dive analyses to support campaigns, lifecycle programs, and go‑to‑market initiatives.
• Other duties as assigned.

Marketing Data Analyst II

• Collaborate with the business, IT, and analytics community to craft opportunities to provide better insights
• Lead and support service line modernization projects from requirement gathering through user-acceptance
• Analyze and create substantial insight for business use and decisions
• Train and support the business in the use of self-service tools and dashboards
• Prepare documentation and analytical reports that summarize results, assumptions, and conclusion

Senior Process Transformation Business Intelligence Data Analyst

• Assist with collecting, organizing, and validating sales and customer data from CRM and other business systems.
• Support the creation and maintenance of reports and dashboards to track sales performance, pipeline activity, and key business metrics.
• Analyze trends and identify opportunities to improve data quality, reporting accuracy, and operational efficiency.
• Prepare summaries and visualizations to support business reviews and leadership decision-making.
• Partner with Sales, Marketing, Customer Success, and Revenue Operations teams on ad hoc projects and analyses.
• Document processes and recommend improvements to reporting and data management practices.

Summer Intern – Sales Operations Data Analyst

• Own the end-to-end delivery of audience segmentation requests from Demand Generation teams
• Manage intake through Workfront, scoping requirements
• Build audience segments in Treasure Data and activate to downstream channels
• Manage the active request queue, maintaining delivery against agreed timelines
• Build audience segments directly in Treasure Data CDP, applying sound segmentation logic
• Develop working knowledge of the CDP data structure
• Work with AI-assisted audience generation via Treasure Data Audience Agent
• Apply consistent quality checks to all audience outputs
• Identify and escalate data quality issues within the CDP
• Maintain thorough documentation of segment definitions and QA outcomes
• Communicate with Demand Generation teams on requirements and any data constraints

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