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Data Scientist

Job in Los Angeles, Los Angeles County, California, 90079, USA
Listing for: LegalZoom.com, Inc.
Full Time position
Listed on 2026-02-22
Job specializations:
  • IT/Tech
    Data Analyst, Business Systems/ Tech Analyst, Data Science Manager
Salary/Wage Range or Industry Benchmark: 100000 - 125000 USD Yearly USD 100000.00 125000.00 YEAR
Job Description & How to Apply Below
Position: Staff Data Scientist

Legal Zoom is on a mission to help people navigate the legal system with confidence and clarity. As a leader in online legal services for over 20 years, we combine technology, attorney-led solutions, and expertise to protect the aspirations, lives, and legacies of millions of customers. If you’re ready to contribute to a collaborative, diverse, and distributed group of creative thinkers and problem-solvers, we can’t wait to meet you.

Candidates must be located in the Mountain View CA or Los Angeles CA area.

Overview

We’re hiring a Staff Data Scientist to partner with our Partnerships team and Finance as a proactive thought leader. The Partnerships team builds and scales acquisition and ecosystem relationships with partner companies, integrating experiences and co‑marketing to drive measurable growth, margin, and customer value. You’ll develop metrics, experiments, and models that power partner onboarding, standardized measurement, pricing strategy, and performance optimization.

You’ll collaborate deeply with Partnerships, Finance, Data Science, Data Engineering, Engineering, and Product to ensure data requirements are captured early and instrumentation is consistent across systems.

You will

Act as a data thought partner to Partnerships and Finance, guiding strategy and prioritization with proactive analysis and clear recommendations.

Lead standardized measurement for partner performance by defining KPIs, building partner scorecards, and operationalizing a single source of truth across dashboards and self-serve tools.

Embed data requirements into the partner lifecycle (from contract discussions through onboarding) to ensure we can reliably measure attribution, conversion, LTV, revenue share, and ongoing ROI.

Drive partner onboarding analytics by aligning tracking and event schemas with Data Engineering, Product, and Engineering; close gaps in attribution and funnel visibility.

Own pricing strategy and optimization analytics (elasticity measurement, price tests, revenue and margin tradeoffs) and advise on deal structures with Finance.

Design and analyze experiments (A/B and multivariate) and run causal inference studies (e.g., diff-in-diff, matching, synthetic control) when randomized tests aren’t feasible.

Build and evolve partner/channel custom attribution approaches (rule-based baselines to model-based methods) that inform spend allocation, partner incentives, and roadmap decisions.

Explore “green-field” opportunities via proactive deep dives, root-cause analyses, and opportunity sizing across the partner ecosystem and in-product experiences.

Ship durable, production-grade analytics and data layers with well-documented pipelines in partnership with Data Engineering.

Communicate insights to partner-facing stakeholders in clear, layperson terms; support adhoc analyses and weekly business review narratives as needed.

You have

7+ years in data science, decision science, or advanced analytics with a track record influencing senior stakeholders and driving measurable business outcomes.

Advanced proficiency in SQL and strong skills in Python for analysis, modeling, and reproducible workflows.

Experience working with modern data stacks including a modern cloud warehouse (e.g. Snowflake), orchestration (e.g. Airflow), attribution analytics (GA4/Segment), version control (Git Hub), BI/visualization (Thought Spot/Tableau), and notebook tools (Hex/Jupyter).

Excellence in data storytelling—able to translate complex findings into crisp, actionable recommendations for non-technical audiences.

Business acumen in pricing, partner economics, and financial modeling, with an ability to collaborate closely with Finance.

Experience partnering with engineers on instrumentation and data quality.

Expertise in metric development and experimentation, including test design, power analysis, and end-to-end evaluation.

Hands‑on experience with causal inference methods and pragmatic application to business decisions.

Familiarity with AI/ML techniques (e.g., uplift modeling, classification/propensity, forecasting) and when to apply them vs. simpler baselines.

Legal Zoom is a remote-friendly company and the national range for this role is…

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