Harvey

<h2>Why Harvey</h2>At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come.This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched.Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you.At Harvey, the future of professional services is being written today — and we’re just getting started.<h2>Role Overview</h2>We’re looking for a versatile Senior Analytics Engineer focusing on Product to architect event data models that power decision-making at Harvey. With product-market fit already proven and demand surging across diverse customer segments, you’ll design clean, reliable pipelines and semantic data models that turn raw events into usable insights. As an Analytics Engineer on our team, you’ll help evolve our data stack, champion best practices in testing and documentation, and collaborate closely with product, GTM, and leadership to ensure every team can answer its own questions with confidence. If you combine engineering rigor with a love of storytelling through data we’d love to meet you.<h2></h2><h2>What You'll Do</h2><ul><li>Design and build scalable data models and pipelines using dbt to transform raw data into clean, reliable assets that power company-wide analytics and decision-making.</li><li>Define and implement a robust semantic layer (e.g. LookML/Omni/Other) that standardizes key business metrics, dimensions, and data products, ensuring self-serve capabilities for stakeholders across teams.</li><li>Partner cross-functionally with Product, GTM, Finance, and the Exec Team to deliver intuitive, consistent dashboards and analytical tools that surface business health metrics.</li><li>Establish and champion data modeling standards and best practices, guiding the organization in how to model data for accuracy, performance, usability, and long-term maintainability.</li><li>Partner with Product Managers, Engineers, and Data teams to design tracking plans for new product surfaces, ensuring events are implemented accurately, consistently, and with downstream analytics use cases in mind.</li><li>Own the product event tracking strategy, including event naming conventions, property schemas, identity resolution, sessionization, versioning, deprecation, and documentation standards.</li><li>Empower stakeholders with data by making analytical assets easily discoverable, reliable, and well-documented – turning complex datasets into actionable insights for the business.</li><li>You’ll define the structure, taxonomy, governance, and modeling patterns for product event data, ensuring that user behavior, product usage, and customer journeys are captured consistently from instrumentation through analytics-ready models.</li></ul><h2></h2><h2>What You Have</h2><ul><li>5+ years of experience in Analytics Engineering, Data Engineering, Data Science, or similar field.</li><li>Deep expertise in SQL, dbt, Python, Snowflake.</li><li>Experience with modern BI tools like (Looker/Omni, or similar).</li><li>Skilled at defining core business and product metrics, uncovering insights, and resolving data inconsistencies across complex systems.</li><li>Strong familiarity with version control (GitHub), CI/CD, and modern development workflows.</li><li>Bias for action – you prefer launching usable, iterative data models that deliver immediate value over waiting for perfect solutions.</li><li>Strong communicator who can build trusted partnerships across Product, GTM, Finance, and Exec stakeholders. Comfortable working through ambiguity in fast-moving, cross-functional environments.</li><li>Balances big-picture thinking with precision in execution – knowing when to sweat the details and when to move quickly.</li><li>Experience modeling high-volume, semi-structured product event data, including JSON payloads, nested properties, user/account identifiers, sessions, funnels, cohorts, and behavioral metrics.</li><li>Experience with product analytics tools (Mixpanel, Segment, Amplitude)</li></ul><h3>Bonus</h3><ul><li>Early employee at a hyper-growth startup</li><li>Experience with or knowledge of AI and LLMs</li><li>Data Engineering Experience</li><li>Experience managing data warehouse (preferably Snowflake)</li><li>Experience at world-class enterprise orgs (ex: Brex, Ramp, Stripe, Palantir)</li></ul><h2></h2><h2>Compensation</h2>$155,800 - $233,600 USD<h3>Depending on your location, an Applicant Privacy Notice may apply to you. You can find all of our Applicant Privacy Notices [<a target="_blank" rel="noopener noreferrer ugc" href="https://www.notion.so/harveyai/Harvey-Candidate-Privacy-Policies-319ac3fcdd7a803bb807d5094f249922">here</a>].</h3>#LI-CD1Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing <a target="_blank" rel="noopener noreferrer nofollow" href="mailto:accommodations@harvey.ai">accommodations@harvey.ai</a>

Senior Analytics Engineer, Product

<h2>Why Harvey</h2>At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come.This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched.Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you.At Harvey, the future of professional services is being written today — and we’re just getting started.<h2>Role Overview</h2>As a Product Data Scientist, you will be a core member of Harvey's product development organization and one of the foundational members of the Data Science function. You will partner with Product, Engineering, Design, Go-to-Market, and company leadership to define how we measure product success, understand user behavior, and make high-quality decisions in a fast-moving environment.This role is both strategic and hands-on. You will define north-star and product-level metrics, design experiments and causal analyses, build source-of-truth reporting, and turn ambiguous product questions into clear recommendations. You should be comfortable operating where the data is imperfect, the product is evolving quickly, and the right answer requires both analytical rigor and strong product judgment.<h2>What You'll Do</h2><ul><li>Embed with Product and Engineering teams as a trusted analytical partner, identifying opportunities to improve user experience, adoption, retention, and business impact.</li><li>Define and maintain core metrics that create a shared understanding of product performance and customer value.</li><li>Design and evaluate experiments, including A/B tests and causal inference methods, to measure the impact of product, model, and workflow changes.</li><li>Analyze product usage, customer segments, and go-to-market signals to surface insights, size opportunities, and inform roadmap decisions.</li><li>Build dashboards, reports, and self-serve tools that help teams answer product questions with confidence.</li><li>Develop models, forecasts, and analytical frameworks to explain user behavior, detect anomalies, and guide prioritization.</li><li>Translate complex analyses into clear recommendations for technical, business, and executive audiences.</li><li>Partner with Engineering and Data teams to improve the infrastructure that powers analytics, experimentation, and decision-making.</li><li>Establish the standards, practices, and culture for Product Data Science at Harvey.</li></ul><h2>What You Have</h2><ul><li>5+ years of experience in data science, product analytics, economics, statistics, or another quantitative field, ideally in a high-growth product company, AI company, research organization, or similarly ambiguous environment.</li><li>A strong track record of using SQL, Python, and statistical methods to answer product questions and turn analysis into product or business impact.</li><li>Experience defining new metrics and measurement frameworks from scratch, especially for products where usage patterns, customer value, or success criteria are still being discovered.</li><li>Deep fluency in experimentation, causal inference, A/B testing, and statistical modeling, with good judgment about when precision matters and when directional clarity is enough.</li><li>Strong product instincts and curiosity about how users adopt, evaluate, and expand their use of AI-enabled workflows.</li><li>Excellent written and verbal communication skills, including the ability to influence Product, Engineering, Go-to-Market, and executive stakeholders through clear reasoning and compelling data stories.</li><li>Comfort creating structure in fast-moving, ambiguous environments and raising the quality of decision-making for the teams.</li></ul>Bonus<ul><li>Experience with AI/ML products, large language models, developer tools, enterprise software, or products used in complex professional workflows.</li><li>Experience as an early data science or analytics hire at a hyper-growth startup, including helping define team norms, tooling, and best practices.</li><li>Experience supporting enterprise or B2B products, including analysis of adoption, engagement, retention, expansion, or go-to-market motion.</li><li>Familiarity with modern data infrastructure and the practical tradeoffs involved in building reliable analytics in a rapidly evolving product environment.</li></ul><h2></h2><h2>Compensation</h2>$155,000 - $260,000<h3>Depending on your location, an Applicant Privacy Notice may apply to you. You can find all of our Applicant Privacy Notices [<a target="_blank" rel="noopener noreferrer ugc" href="https://www.notion.so/harveyai/Harvey-Candidate-Privacy-Policies-319ac3fcdd7a803bb807d5094f249922">here</a>].</h3>#LI-SB1Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing <a target="_blank" rel="noopener noreferrer nofollow" href="mailto:accommodations@harvey.ai">accommodations@harvey.ai</a>

Data Scientist, Product

<h2>Why Harvey</h2>At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come.This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched.Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you.At Harvey, the future of professional services is being written today — and we’re just getting started.<h2>Role Overview</h2>We’re looking for a versatile Senior Analytics Engineer to partner closely with our Finance team in building the financial data foundation that drives decision-making at Harvey. With product-market fit already proven and demand surging across diverse customer segments, you’ll design clean, reliable pipelines and semantic data models that turn source data into usable insights. As an Analytics Engineer on our team, you’ll help evolve our data stack, champion best practices in testing and documentation, and collaborate closely with product, finance, and leadership to ensure every team can answer its own questions with confidence. If you combine engineering rigor with a love of storytelling through data we’d love to meet you.<h2></h2><h2>What You'll Do</h2><ul><li>Design and build scalable data models and pipelines using dbt to transform raw data into clean, reliable assets that power company-wide financial analytics and decision-making.</li><li>Define and implement a robust semantic layer (e.g. LookML/Omni/Other) that standardizes financial and operating metrics, including revenue, retention, customer growth, usage, margin, and forecast inputs.</li><li>Partner cross-functionally with Product, Finance, and the Exec Team to deliver intuitive, consistent dashboards and analytical tools that surface business health metrics (ARR, NRR).</li><li>Establish and champion data modeling standards and best practices, guiding the organization in how to model data for accuracy, performance, usability, and long-term maintainability.</li><li>Lead data governance initiatives, ensuring high standards of data quality, consistency, documentation, and access control across the analytics ecosystem.</li><li>Structure financial metric definitions, business logic, and accounting context in ways that can support AI-assisted reporting, natural language analytics, and automated anomaly detection.</li></ul><h2>What You Have</h2><ul><li>5+ years of experience in Analytics Engineering, Data Engineering, Data Science, or similar field.</li><li>Deep expertise in SQL, dbt, Python, Snowflake.</li><li>Experience with modern BI tools like (Looker/Omni, or similar).</li><li>Skilled at defining core financial and operating metrics, uncovering insights, and resolving data inconsistencies across complex systems.</li><li>Strong familiarity with version control (GitHub), CI/CD, and modern development workflows.</li><li>Bias for action – you prefer launching usable, iterative data models that deliver immediate value over waiting for perfect solutions.</li><li>Strong communicator who can build trusted partnerships across Finance, GTM, Product, and Exec stakeholders.</li><li>Comfortable working through ambiguity in fast-moving, cross-functional environments.</li><li>Balances big-picture thinking with precision in execution — knowing when to sweat the details and when to move quickly.</li><li>Experience modeling financial, billing, subscription, CRM, or usage-based revenue data.</li><li>Strong understanding of business metrics such as ARR, MRR, churn, retention, expansion, bookings, billings, and revenue recognition.</li></ul><h2>Bonus</h2><ul><li>Early employee at a hyper-growth startup</li><li>Experience with or knowledge of AI and LLMs</li><li>Data Engineering Experience</li><li>Experience managing data warehouse (preferably Snowflake)</li><li>Experience at world-class enterprise orgs (ex: Brex, Ramp, Stripe, Palantir)</li></ul><h2>Compensation</h2>$155,000 - $235,000 USD<h3>Depending on your location, an Applicant Privacy Notice may apply to you. You can find all of our Applicant Privacy Notices [<a target="_blank" rel="noopener noreferrer ugc" href="https://www.notion.so/harveyai/Harvey-Candidate-Privacy-Policies-319ac3fcdd7a803bb807d5094f249922">here</a>].</h3>#LI-CD1Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing <a target="_blank" rel="noopener noreferrer nofollow" href="mailto:accommodations@harvey.ai">accommodations@harvey.ai</a>

Senior Analytics Engineer, Finance

<h2>Why Harvey</h2>At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come.This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched.Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you.At Harvey, the future of professional services is being written today — and we’re just getting started.<h2>Role Overview</h2>We’re hiring a Marketing Data Scientist to partner closely with Harvey’s Marketing organization and build our marketing data science function from the ground up. In this role, you’ll serve as a trusted analytical partner to Marketing, GTM, and Finance - defining how we measure marketing success, understanding what drives channel and campaign performance, and informing where and how we invest to accelerate growth. As one of the earliest Marketing data science hires, you’ll own the development of core Marketing metrics, scalable dashboards, and analytical frameworks that enable data-driven decision-making across the business.<h2>What You’ll Do</h2><ul><li>Embed deeply with the Marketing organization as a trusted partner, identifying opportunities to improve performance and drive growth.</li><li>Define, track, and evolve core metrics across marketing and business functions, building scalable dashboards and reporting frameworks that enable data-driven decision-making.</li><li>Design, implement, and evaluate models (multi-touch attribution, marketing mix modeling, incrementality) for comprehensive Marketing Channel and Campaign performance and contribution.</li><li>Apply statistical and machine learning techniques to model user behavior, forecast trends, and identify opportunities for growth and optimization.</li><li>Translate complex analyses into compelling stories, delivering clear recommendations to cross-functional partners and executives.</li><li>Partner with Marketing, RevOps and GTM System, to co-develop data infrastructure, ensuring robust pipelines, reliable data sources, and scalable systems that power analytics and modeling.</li><li>Lead cross-functional analytics initiatives that synthesize competitive dynamics, customer feedback, and market trends into actionable opportunities for the business.</li><li>Champion a data-informed culture by establishing best practices, mentoring peers, and shaping the strategic role of data science at Harvey.</li></ul><h2>What You Have</h2><ul><li>5+ years of experience in quantitative roles operating in highly ambiguous environments, ideally as an early data scientist or Marketing analyst within a hyper-growth product company or research organization</li><li>Expertise in SQL, with extensive experience extracting large datasets and designing ETL workflows</li><li>Expertise working with Salesforce, Marketo and Ads spent data</li><li>Strong experience with modern data stack, such as DBT, Looker and Omni</li><li>Proficiency in quantitative programming languages, such as Python and R</li><li>Experience defining, implementing, and operationalizing Marketing campaign- and channel-level metrics from the ground up</li><li>Strong communication skills, with the ability to effectively partner with leaders across Marketing, GTM and Finance</li><li>Strategic mindset capable of generating insights that extend beyond traditional statistical significance testing to inform long-term product and business direction</li></ul><h2>Compensation</h2>$170,000 - $260,000 USD<h3>Depending on your location, an Applicant Privacy Notice may apply to you. You can find all of our Applicant Privacy Notices [<a target="_blank" rel="noopener noreferrer ugc" href="https://www.notion.so/harveyai/Harvey-Candidate-Privacy-Policies-319ac3fcdd7a803bb807d5094f249922">here</a>].</h3>#LI-SB1Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing <a target="_blank" rel="noopener noreferrer nofollow" href="mailto:accommodations@harvey.ai">accommodations@harvey.ai</a>

Harvey

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Senior Analytics Engineer, Product

Data Scientist, Product

Senior Analytics Engineer, Finance

Data Scientist, Marketing

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