Data Analyst

• Build a cohesive view of Harvey's employee lifecycle — connecting recruiting, onboarding, engagement, performance, mobility, retention, and exits into a single, actionable narrative that shows where exceptional talent thrives or breaks down
• Own the vision and roadmap for Harvey's people data infrastructure — partner with Data Engineering and Security to stand up the people data layer in Snowflake (or similar), define architecture requirements, and drive role-based access controls and data governance so the right people have the right access
• Consolidate workforce data across Workday, Ashby, Envoy, Culture Amp, and other HR systems, and build the data quality frameworks that keep it trustworthy at scale
• Define and maintain Harvey's people metrics dictionary — standardize how headcount, attrition, hiring, and workforce trends are measured across the org
• Design the frameworks and methodologies that scale beyond v1 — forecast headcount, model attrition, segment the org, benchmark against market — built to explain not just *what* is happening but *why*
• Move People Analytics beyond reporting into intervention — surface leading indicators, manager behaviors, operational friction, and emerging org risks before they become scaled people problems, and help Harvey understand what attracts, enables, retains, and risks losing exceptional talent
• Build dashboards that give leadership clear visibility into the workforce, cuttable by org, region, and function — and shape exec-level decisions with the insights they surface
• Build the self-service foundation that lets partner teams operate independently — design the frameworks, tooling, and documentation so that comp, PBPs, and other partners can surface their own insights without routing every question through analytics
• Drive alignment across PBPs, RecOps, People Systems, and Finance to define reporting cadence and answer the questions that drive strategic people decisions
• Set the bar for people data craft at Harvey — define standards, review work, and grow the analytics capability of partner teams
• Use AI aggressively to automate workflows, accelerate analysis, and scale your impact — this is a role where AI-first thinking compounds fast

People Data Analytics Lead

• 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

Customer Data Analyst

• Influence and contribute to the design and development of data services in support of ECAH.
• Define user stories and validate the impact of changes to datasets and data models.
• Break up complex work into digestible work elements with knowledge of agile methodologies.
• Navigate integrated enterprise data and work across multi-functional teams.

Principal Data Analyst

• Analyze Snowflake, cloud, and data platform billing data to identify spend drivers, usage trends, and cost optimization opportunities
• Build, maintain, and interpret dashboards, KPIs, and reporting that enable cost transparency, showback, and future chargeback
• Partner with engineering and product teams to explain cost variance, validate optimization recommendations, and support architectural trade-off decisions
• Support financial planning activities, including forecasting, budgeting, and variance analysis, in close alignment with Finance
• Contribute to cloud and platform cost governance by monitoring utilization, identifying risks, and tracking savings initiatives
• Produce clear, credible insights and narratives that enable informed cost decisions across technical and financial audiences
• Support ongoing improvement of FinOps processes, tooling, and data quality
• Participate in recurring reviews of spend, trends, and investment priorities with cross-functional stakeholders

FinOps Data Analyst – Cost Insight, Business Alignment

• Collect, process, cleanse, and validate data from multiple internal and external sources.
• Define, maintain, and improve data rules, mappings, transformations, and interface requirements.
• Identify, investigate, and resolve data discrepancies across systems to improve accuracy, consistency, and reliability.
• Monitor data quality, hierarchy integrity, and matching outcomes; recommend scalable corrective actions and logic improvements.
• Support production data processes across the lifecycle, including pre-production validation, production issue resolution, and post-production monitoring.
• Partner with business, analytics, and technology teams to ensure trusted data supports reporting, segmentation, and decision-making.
• Contribute to automation and advanced data quality initiatives that reduce manual rework, operational risk, and downstream escalations.
• Translate data issues into business impact and prioritize improvements that enhance efficiency, accuracy, and scalability.

Lead Data Analyst

• Play a meaningful role in delivering high-quality, impactful analytics and insights to Talent, HR and business leaders.
• Lead efforts to transform candidate, associate, and operational data into actionable insights that inform strategic decision-making across Talent Acquisition, Talent Management, and Talent Learning and Development.
• Design and implement data workflows, models, and dashboards that make talent data accessible, interpretable, and impactful.
• Support workforce data initiatives, ensuring analytics solutions are aligned with business needs and delivered efficiently.
• Uncover trends, tell compelling data stories, and translate complex analytics into business recommendations.
• Develop and maintain robust data pipelines using SQL (Snowflake, SQL Server), with a focus on performance tuning and query optimization.
• Create and enhance interactive dashboards and visualizations in Tableau and Power BI to support leadership with real-time insights and compelling data storytelling.
• Collaborate cross-functionally with Talent and Business leaders to gather requirements, translate business needs into analytics solutions, and deliver insights that influence strategic decisions.
• Communicate and socialize analytical findings by translating complex data into clear, actionable business recommendations through presentations and storytelling.
• Provide mentorship and thought leadership to team members and cross-functional partners, fostering a culture of analytical excellence and continuous learning.

Senior Manager, Data Analytics, Insights

• Leads a team of analysts for strategic data projects
• Hires, evaluates, and supervises crew
• Oversees data analysts working with key stakeholders to understand business strategy
• Provides expert consulting for actionable solutions
• Collects, analyzes, and communicates statistics
• Develops processes and relationships for data project management

Manager, Data Analytics – Reporting

• Analyze Loopback’s large-scale healthcare data warehouse (claims, EHR, pharmacy, etc.) to support answering clinical research feasibility questions across various therapy areas.
• Assist in developing reporting tools that help non-technical stakeholders understand the data asset.
• Synthesize and communicate analytical findings to team members.
• Collaborate with Sales, Client Success, Product, and Operations teams to improve data quality, documentation, and product features.
• Gather and document customer feedback to inform future data product development.

RWD Data Analyst

• Collect, clean, and analyze data from multiple sources using tools like SQL, Excel, Python, or Tableau
• Identify patterns, trends, and correlations to support descriptive, diagnostic, predictive, and prescriptive analytics
• Assist with creation of branding, communication, and training materials
• Translate complex data findings into clear, concise, communications for diverse audiences
• Develop and maintain digital asset libraries (e.g., multimedia content, documents) for easy retrieval and reuse

Technical Communications, Data Analyst

• Coordinate, support and operationalize data collection to enhance AI performance
• Build and maintain dashboards (e.g., Pendo, Qualtrics) to track user behavior, experience metrics, and KPIs
• Aggregate and synthesize quantitative and qualitative data into clear, actionable insights
• Analyze user behavior and feedback to identify trends, issues, and opportunities for experience improvement
• Support VOC initiatives by organizing, maintaining, and evolving insights repositories
• Leverage analytics to inform product decisions and optimize user experience
• Assist with survey design, data preparation, and analysis for research initiatives
• Support in communicating insights and recommendations to stakeholders, including product, design, and business leaders
• Recommend and implement best practices for data instrumentation and tool usage
• Document insights, dashboards, and methodologies for ongoing team use
• Manage and prioritize multiple requests and projects
• Explore and evolve advanced analytics capabilities (ex:, AI-driven insights, cross-platform data integration, API connections) to continuously enhance experience intelligence.
• Travel approximately 3-4 times per year for key meetings

Data Analyst, Voice of Customer

• Define and execute the PW data product strategy, aligned with business priorities and digital transformation goals
• Oversee the end-to-end lifecycle of data products—from ideation and design to delivery, scaling, and retirement
• Design and operationalize a federated, domain-oriented data product model
• Lead and develop a high-performing team of data product managers, product owners, and analysts
• Enable development of AI-ready data products to accelerate advanced analytics, machine learning, and generative AI use cases
• Define and track business value metrics tied to revenue growth, cost efficiency, risk reduction, and client experience.

Senior Manager, Data Analytics – Management

• Design and develop the analytical engine for a decision product
• Apply causal inference techniques
• Leverage predictive modeling and optimization approaches
• Translate complex business questions into structured analytical frameworks

Senior Data Analyst, Data Scientist – Decision Analytics, Modeling

• Support ARR modelling, forecasting, and variance analysis across the business
• Develop and maintain customer account stratification frameworks (by size, industry, engagement, health score, etc.)
• Monitor customer activities and engagement patterns to identify trends and opportunities
• Analyze drivers of New Logo ARR, Expansion, Contraction, and Churn
• Build predictive models for revenue forecasting and customer behavior
• Build and maintain KPI metrics including: Annual Recurring Revenue (ARR), Net Revenue Retention (NRR), Gross Revenue Retention (GRR), Customer Acquisition Cost (CAC), and Lifetime Value (LTV)
• Design and implement dashboards and reporting systems that serve as the single source of truth for business performance
• Build and maintain executive dashboards using Power BI and other BI tools
• Ensure data accuracy and consistency across all revenue systems (CRM, billing, product analytics, etc.)
• Create board-ready reporting packages for executive leadership
• Establish and document data governance standards and best practices
• Perform data validation, reconciliation, and anomaly detection across systems
• Highlight growth opportunities, risk areas, and efficiency improvements
• Conduct cohort analyses, retention studies, and revenue waterfall analyses
• Partner with Sales, Customer Success, Product, and Finance teams to drive data-informed decisions
• Supporting optimization of end-to-end SaaS reporting
• Partner with RevOps and Sales leadership to ensure metric alignment and data accuracy
• Develop and maintain documentation for data definitions, metrics, and processes
• Continuously improve data collection, processing, and reporting workflows

Lead Revenue and Data Analyst

• Perform statistical analysis to evaluate test results, including significance testing and confidence interval calculations.
• Build and maintain dashboards reporting the health of our ecommerce experiences
• Work directly with product teams to help identify and prioritize opportunities to improve our digital ordering process
• Support our A/B testing processes with analytics
• Build presentations explaining conclusions from analytics and present results to stakeholders

Digital Data Analyst

• Own and operate a centralized reporting intake and delivery process, partnering with cross‑functional teams to define reporting needs
• Design, develop, and maintain automated reporting solutions that improve efficiency, accuracy, and scalability
• Build high‑quality dashboards, reports, and visualizations that clearly communicate insights and trends
• Deliver insights related to GenAI programs, translating complex data into meaningful narratives for operational and executive audiences
• Support digitalization initiatives by modernizing reporting workflows and reducing manual processes
• Collaborate with business partners to ensure reports align to decision‑making needs and business priorities
• Present findings, insights, and recommendations clearly and confidently to leadership at multiple levels
• Continuously improve reporting standards, visualization quality, and presentation effectiveness

• Maintain the KPI standards for Customer Support: document how each metric is calculated and interpreted, keep definitions current across data platforms, and flag to leadership when targets may need adjustment.
• Build and maintain dashboards in Omni Analytics (our BI platform) that serve analyst, manager, and leadership audiences; maintain the semantic layer and metric definitions so every team measures the same things the same way.
• Produce formal analyses and recommendations on volume trends, resolution efficiency, CSAT, contact rate, and cost performance; frame findings in terms of business impact, not just numbers.
• Identify anomalies and performance gaps in Support data; bring a recommended course of action to leadership rather than a flag, and track the response through to resolution.
• Consult on SQL, Snowflake, and BI standards used for Support reporting; ensure Support modeling approach, query patterns, and tooling match organizational standards.
• Lead metric alignment conversations with Data, Product, and Engineering; represent Support's analytical interests and keep shared definitions from drifting.
• Triage and scope ad hoc analysis requests from across the organization; exercise judgment on urgency, feasibility, and which questions are worth answering.

• Applies developed subject matter knowledge to solve common and complex business issues
• Participates as a member of a team of other data science engineers carrying out the investigation, design, development, execution, and implementation of data science projects
• Creates plans, data collection and analysis procedures and data insight visualizations for assigned projects
• Collaborates with internal and external partners to perform experiments and validations in accordance with overall plan
• Prepares literature and presentations for peer review, publication, and delivery at industry and scientific events and conferences
• Provides guidance and mentoring to less-experienced staff members

• Participates as a member of team of other data science engineers carrying out the investigation, design, development, execution, and implementation of data science projects to generate new insights, products, technologies, and intellectual property.
• Creates plans, data collection and analysis procedures and data insight visualizations for assigned projects.
• Collaborates with internal and external partners to perform experiments and validations in accordance with overall plan.
• Collaborates with SMEs to develop procedures for collecting, recording, analyzing, and communicating data for review and feedback.
• Prepares literature and presentations for peer review, publication, and delivery at industry and scientific events and conferences; creates patent applications and supporting documentation.
• Provides guidance and mentoring to less-experienced staff members.

• Lead end-to-end data analysis projects supporting divisional priorities while contributing to broader enterprise initiatives that influence business performance and member outcomes.
• Leverage advanced analytical techniques, industry research, and business knowledge to uncover trends, opportunities, and recommendations for strategic decision-making.
• Partner with stakeholders to identify opportunities for cost reduction, revenue growth, operational efficiency, and enhanced member experiences.
• Take ownership of the debit analytics ecosystem, redesigning and modernizing reporting capabilities to create scalable, actionable insights for product leaders and business partners.
• Transform complex data from multiple sources into meaningful business intelligence that supports product innovation and strategic planning.
• Design scalable dashboards and reporting solutions for informed organizational decision-making.
• Translate complex analyses into clear, actionable recommendations through visualizations and presentations.
• Guide teams through experimental design and interpretation of results with A/B testing efforts.
• Continuously refine KPIs, reporting methodologies, and performance measurement practices to improve visibility.
• Create reusable transformation logic and scalable datasets using Snowflake and advanced SQL techniques.
• Identify opportunities to enhance data infrastructure and workflows.
• Mentor and develop others within the analytics community, promoting best practices and analytical standards.

Senior Data Analyst

• lead the development of Human Resources (HR) data foundations, analytic solutions and prioritized research requests
• advancing Fidelity’s use of HR data and tools to advance people-related strategies
• manage the delivery of analytics projects
• build stakeholder relationships with HR and business leadership
• develop and deliver presentations that communicate key findings

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People Data Analytics Lead

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Manager, Data Analytics – Reporting

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Data Analyst

Data Analyst

Data Analyst

Data Analyst

Senior Data Analyst

Director, Data Analytics and Insights