Data Analyst

Everlaw is looking for a Data Analyst who transforms raw data into the actionable insights our leadership needs to steer the company forward. Everlaw is at the forefront of legal technology, dealing with massive, complex datasets to help legal teams uncover the truth in high-stakes litigation. Data is absolutely critical in helping our company navigate complex use cases, sophisticated user workflows, and the operational challenges of a high-growth, AI native SaaS business.

You’ll collaborate with Senior Data Scientists, Product Managers, GTM leadership, Software Engineers, and many other partners to dive into our data ecosystem and monitor product performance, track user engagement, and identify trends that inform our company’s strategic roadmap. You will be responsible for ensuring our data remains a "source of truth" by maintaining rigorous quality standards and building intuitive dashboards that democratize information across the company. As a team, we highly value innate curiosity, an eye for detail, and a preference for solving problems collaboratively.

At Everlaw, engineering is key to our mission. Our company culture is open and vibrant and we’re committed to the professional growth of our team members, offering an annual learning and development stipend and regular check-ins with managers regarding career goals. If you’re looking for a place that values passion, integrity, thinking big, and a desire to learn, we’d love to hear from you! Think you’re missing some of the skills and are hesitant to apply? We do not believe in the ‘perfect’ candidate and encourage you to apply if you feel you can bring value to our team.  

This is a full-time, exempt position located onsite (3 days/week in office) in Oakland, California.

• We want you to feel like part of the team early on! Our onboarding process will integrate you into the company with informative sessions on our product, policies, processes, and team structure and goals.
• We’re excited for you to learn, grow, and contribute right away! We trust that you’ll bring industry experience and knowledge that will uplift and uplevel the team, but we don’t expect you to know everything on Day 1.

• Familiarize yourself with our technologies, workflows, and codebase through extensive training and product certification.
• Transform large datasets into actionable metrics and attributes using SQL and Spark.
• Explore and develop the right repeatable methods for mining insight from large unstructured datasets, leveraging a variety of tools spanning Jupyter notebooks, Looker, and Heap.
• Design and surface metrics that are faithful and precise, while helping the business understand how to drive those metrics.
• Build out the data context layer (schemas, metric definitions, institutional knowledge, etc.) to power agentic analytics workflows.
• Advise business teams on how to implement scalable, robust telemetry and analytics tracking.

• A Bachelor’s degree in a quantitative field such as Statistics, Mathematics, Computer Science, Economics, or a related technical discipline.
• Up to 4 years of experience (including internships) turning large datasets into actionable business insights.
• Experience and proficiency wrangling data using SQL.
• Experience and proficiency in applying scientific programming languages (Python, R, Julia, etc.) to data analysis problems.
• Understanding of the fundamentals of relational databases and data modeling.
• Strong foundation of statistical methods and probability theory.
• Excellent communication and presentation skills, especially in translating technical information to non-technical audiences.

• Experience working with common open source analytics tools such as Airflow or DBT.
• Experience working with distributed processing technologies such as Spark or MapReduce.
• Experience applying machine learning or statistical modeling methods to real world problems.
• Familiar with Git or a similar DVCS.