Job Description
EvenUp is on a mission to close the justice gap using technology and AI. We empower personal injury lawyers and victims to get the justice they deserve. Our products enable law firms to secure faster settlements, higher payouts, and better outcomes for victims injured through no fault of their own in vehicle collisions, accidents, natural disasters, and more.
We are one of the fastest-growing vertical SaaS companies in history, and we are just getting started. EvenUp is backed by top VCs, including Bessemer Venture Partners, Bain Capital Ventures, SignalFire, and Lightspeed. We are looking to expand our team with talented, driven, and collaborative individuals who seek to have a lasting impact. Learn more at
About the team: The Analytics team at Evenup plays a critical role in driving data-informed decision-making across the organization. We partner closely with Product, Engineering, Operations, and Executive teams to uncover insights, build scalable data solutions, and enable a culture of data-driven decision making and continuous improvement. Our team is responsible for everything from foundational data modeling and reporting to advanced analytics and forecasting.
We are looking for a curious, impact-driven early career
Economist / Data Scientist to join our fast-paced, data-driven team. You’ll work at the intersection of data, economics, and strategy to drive high-impact decisions across pricing, growth, and product monetization. You will apply your expertise in causal inference, econometrics, and behavioral analysis to answer some of the most critical questions in our business, and shape the way we use economics and data science to drive long-term value.
The ideal candidate for this role may be a recent economics PhD graduate with relevant research experience, typically in computationally intensive empirical topics, as well as some exposure to data management and data science. More senior candidates are also welcome to apply.
Please Note: This is a hybrid role with the expectation of working at least 3 days a week from one of our office hubs in San Francisco or Toronto.
What You'll Do - Translate complex datasets into clear insights with strategic recommendations that drive measurable actions and outcomes to inform product direction and business priorities
- Partner with Product, and Ops teams to define KPIs and lead the analytics strategy for key product areas, including causal inference, cohort analysis, retention modeling and experimentation design
- Develop forecasts for ARR, conversion, churn, and usage using economic and behavioral data
- Collaborate with data engineering, analytics, and product to shape best practices in experimentation, forecasting, and decision support
What We’re Looking For We’re looking for someone with deep expertise in both economics and applied data science with the ability to frame business questions into well-scoped analytical or modeling problems.
- Graduate-level research experience on data-intense problems or 1+ years of industry experience in machine learning or economics-focused roles
- A blend of economic theory, applied econometrics, and business skills that let you jump into a fast-paced environment and contribute from day one
- Proven ability to identify and measure causal business impacts using appropriate statistical techniques, especially in complex or observational settings
- Strong engineering skills with expertise in R or Python and fluency in data manipulation (SQL, Pandas) and machine learning (scikit-learn, XGBoost, Keras/Tensorflow) tools
- An ability to identify and prioritize high-impact problems and deliver solutions that provide reasonable trade-offs between urgency and quality
- Strong verbal and written communication skills - ability to distill complex findings from models and economic reasoning into compelling insights and communicate effectively with technical and non-technical audiences
Bonus Points - Prior full time or intern experience in SaaS or B2B subscription businesses and/or in the legal domain
- Familiarity with experimentation platforms (e.g., Optimizely, internal tools) and BI tools (e.g., Looker, Tableau)
Notice to Candidates: EvenUp has been made aware of fraudulent job postings and unaffiliated third parties posing as our recruiting team – please know that we have no affiliation or connection to these situations. We only post open roles on our career page (evenuplaw.com/careers) or reputable job boards like our official LinkedIn or Indeed pages, and all official EvenUp recruitment emails will come from the domains @evenuplaw.com, @evenup.ai, @ext-evenuplaw.com,
[email protected] or no‑
[email protected] email addresses.
To ensure fairness and proper consideration, we do not accept resumes or expressions of interest via email or social media messages. If you’re interested in a role, please submit your application directly through our careers page.
If you receive communication from someone you believe is impersonating EvenUp, please report it to us at [email protected]. Examples of fraudulent domains include “careers-evenuplaw.com” and “careers-evenuplaws.com”. Benefits & Perks: As part of our total rewards package, we offer attractive benefits and perks to our employees, including:
- Choice of medical, dental, and vision insurance plans for you and your family
- Additional insurance coverage options for life, accident, or critical illness
- Flexible paid time off, sick leave, short-term and long-term disability
- 10 US observed holidays, and Canadian statutory holidays by province
- A home office stipend
- 401(k) for US-based employees and RRSP for Canada-based employees
- Paid parental leave
- A local in-person meet-up program
- Hubs in San Francisco and Toronto
Please note the above benefits & perks are for full-time employees EvenUp is an equal opportunity employer. We are committed to diversity and inclusion in our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. Compensation Range: $145K - $220K
Job Tags
Full time, Temporary work, Internship, Work at office, Local area, Home office, Flexible hours, 3 days per week,