Laurel · 14 hours ago
Senior ML Data Scientist, Analytics
San Francisco, CA
Full-time
Hybrid
Mid, Senior Level
$175K/yr - $240K/yr
3+ years expLaurel is on a mission to return time by transforming how organizations capture, analyze, and optimize their most valuable resource: time. As a Senior ML Data Scientist, Analytics, you will build the analytical and modeling foundation to enable fast, confident, and measurable decisions, partnering closely with Product and Engineering teams to embed analytics and ML evaluation into every release.
Artificial Intelligence (AI)LegalMachine LearningProfessional ServicesSaaSSoftware
No H1B
Responsibilities
Define, standardize, and own key product and model success metrics
Build and maintain canonical tables and metric definitions in Laurel’s Analytics Data Warehouse as the trusted source of truth for product and ML evaluation
Contribute to the feature store and ensure features are well-defined, versioned, and measurable
Partner with Product Managers to define success criteria of AI features, guardrails, and evaluation plans before features and models ship
Lead rigorous evaluation of product features and ML-driven functionality: Did it work? For whom? Why?
Apply and interpret metrics such as precision/recall, ROC curves, calibration, clustering quality, and offline vs. online performance
Partner with the AI team to monitor model behavior over time and connect model performance to user experience and business outcomes
Build dashboards, alerts, and self-serve tools that enable teams to quickly understand changes in model performance and how those changes affect users
Proactively surface insights when metrics materially change, rather than reacting to user feedback
Design, prototype, and iterate on applied ML models (e.g., classification, clustering, ranking) to support new product capabilities, improve existing AI features, and inform production model development
This includes feature engineering, establishing baselines, performing error analysis, and partnering with Engineering to productionize successful approaches
Qualification
Required
Bachelor's degree in Computer Science, Engineering, Statistics, or a related field, or equivalent practical experience
3+ years of professional experience as a Data Scientist
Advanced SQL and Python
Experience with data orchestration tools (e.g., Airflow)
Experience with Git/GitHub
Experience with building and evaluating ML models
Familiarity with data modeling, warehousing principles, and BI tools (e.g., Thoughtspot, Mode Analytics)
Strong problem-solving and communication skills
Ability to work in a fast-paced startup environment and manage multiple priorities
Preferred
Experience with experimentation platforms (LaunchDarkly, in-house frameworks)
Benefits
Generous equity
Comprehensive medical/dental/vision coverage with covered premiums
401(k)
Additional benefits including wellness/commuter/FSA stipends
Company
Laurel
Laurel automates timesheet management for legal and accounting firms using AI.
51-200 employees
Funding
Current Stage
Growth StageTotal Funding
$155.7MKey Investors
IVPUpfront Ventures
2025-06-10Series C· $80M
2025-06-10Secondary Market· $20M
2022-03-01Series B· $36.5M
Leadership Team
Ryan Alshak
CEO
Kourosh Zamani
Co-Founder, Strategic Growth & Partnerships
Recent News
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2026-02-03
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