Laurel is on a mission to return time. As the leading AI Time platform for professional services firms, weâre transforming how organizations capture, analyze, and optimize their most valuable resource: time. Our proprietary machine learning technology automates work time capture and connects time data to business outcomes, enabling firms to increase profitability, improve client delivery, and make data-driven strategic decisions. We serve many of the world's largest accounting and law firms, including EY, Aprio, Crowell & Moring, and Frost Brown Todd, and process over 1 billion work activities annually that have never been collected and aggregated before Laurelâs AI Time platform.
Our team comprises top talent in AI, product development, and engineeringâinnovative, humble, and forward-thinking professionals committed to redefining productivity in the knowledge economy. We're building solutions that empower workers to deliver twice the value in half the time, giving people more time to be creative and impactful. If you're passionate about transforming how people work and building a lasting company that explores the essence of time itself, we'd love to meet you.
About the Role
As a Senior Data Scientist, Product Analytics, you will build the analytics foundation that enables Laurelâs Product, Engineering, and Executive teams to make fast, confident, and measurable decisions.
You will own the full product analytics lifecycle: defining product success metrics, shaping instrumentation strategies, building canonical datasets, designing core funnels and retention models, and translating findings into clear, actionable direction. Youâll partner closely with Product and Engineering to embed analytics into every release, ensuring Laurel understands whatâs working, what isnât, and why.
This is a high-ownership, 0â1 role. You wonât just answer questions. Youâll define the questions, build the frameworks to answer them at scale, and help operationalize Product Analytics as a core capability of the company.
You should be deeply analytical, fluent in SQL and Python, and highly comfortable using data to explain behavior, measure impact, and guide product strategy. You are expected to ship production-grade code and contribute to our shared analytics codebase in a thoughtful, maintainable way.
This role does not require dedicated ML research responsibilities. However, it is a strong plus if you understand how to evaluate AI/ML models in real-world products. This may include helping define model success metrics, building dashboards that monitor model performance in production, and partnering with the AI team to translate model performance into business impact.
What you will do
Build Core Product Analytics
Define, standardize, and maintain key product metrics (activation, retention, churn predictors, product feature success criteria, engagement indicators).
Build canonical tables in Laurelâs Analytics Data Warehouse that become the trusted source of truth.
Own Feature Measurement & Decision Science
Partner with PMs to define success metrics, guardrails, and experiment decision frameworks before features ship.
Lead meaningful evaluation: âDid the feature actually improve user experience?â
Build Funnels, Retention & Behavior Understanding
Develop canonical end-to-end funnels: onboarding â first success â habit formation â retained power usage.
Identify leading indicators of retention and churn.
Uncover insights that drive roadmap prioritization and feature development
Ship actionable dashboards; proactively alert teams when behavior materially changes
Raise data quality & instrumentation
Add validation tests and monitoring, triage data issues quickly, and collaborate with Product/Engineering to improve data quality.
Help Operationalize the Product Analytics Function
Establish best-practice processes, templates, cadence, and expectations across Product.
Partner closely with Data Engineering/Data Infra to shape the analytics warehouse and metric layers
You will be a great fit if you have
Education: Bachelor's degree in Computer Science, Engineering, Statistics, or a related field, or equivalent practical experience.
Experience: 3+ years of professional experience as a Data Scientist. Ideal candidates will be comfortable working with large-scale data systems.
Technical Proficiency:
Advanced SQL and Python
Experience with data orchestration tools (e.g., Airflow).
Experience with Git/GitHub
Proficiency in modern data warehouses (e.g., Clickhouse).
Familiarity with data modeling, warehousing principles, and BI tools (e.g., Thoughtspot, Mode Analytics).
Soft Skills:
Strong problem-solving and communication skills.
Ability to work in a fast-paced startup environment and manage multiple priorities.
Nice to haves
Experience with experimentation platforms (LaunchDarkly, in-house frameworks).
Experience with building and evaluating ML models
Flexibility and Logistics
Location: This role will be hybrid based in our San Francisco office, 3 days per week. We will consider exceptionally qualified candidates based in other US-locations on a case by case basis.
Compensation: Competitive salary, generous equity, comprehensive medical/dental/vision coverage with covered premiums, 401(k), additional benefits including wellness/commuter/FSA stipends. For candidates based in San Francisco the compensation range for this role is $175,000-$240,000 USD. Final compensation amounts will be determined based on several factors including candidate experience, qualifications and expertise and may vary from the amounts listed.
Visa Sponsorship: Unfortunately we are unable to provide Visa Sponsorship at this time.
To date, we've secured significant funding from renowned venture capitalists (Google Ventures, IVP, Anthos, Upfront Ventures), as well as notable individuals like Marc Benioff, Gokul Rajaram, Kevin Weil, and Alexis Ohanian
A smart, fun, collaborative, and inclusive team
Great employee benefits, including equity and 401K
Bi-annual, in-person company off-sites, in unique locations, to grow and share time with the team
An opportunity to perform at your best while growing, making a meaningful impact on the company's trajectory, and embodying our core values: understanding your "why," dancing in the rain, being your whole self, and sanctifying time
We encourage diverse perspectives and rigorous thinkers who aren't afraid to challenge the status quo. Laurel is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status. We are not able to support visa sponsorship or relocation assistance.Â
If you think you'd be a good fit for this role, we encourage you to apply, even if you donât perfectly match all the bullet points in the job description. At Laurel, we strive to create an inclusive culture that encourages people from all walks of life to bring their unique, diverse perspectives to work. Every day, we aim to build an environment that empowers us all to do the best work of our careers, and we can't wait to show you what we have to offer!
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