Data Scientist

Location

Toronto (hybrid)

Full time

Hybrid

Data Science

• Estimated Base Salary CA $205,000 – CA $235,750
  • Offers Equity

The salary range provided reflects the compensation that Even Up reasonably expects to offer for this role. The specific salary within this range will be determined based on various factors, including the candidate's relevant experience, education, skills, location, and alignment with the role's responsibilities.

Even Up 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. Even Up is backed by top VCs, including Bessemer Venture Partners, Bain Capital Ventures, Signal Fire, 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

This is a hybrid role, with an expectation of being in one of our Toronto office at least three days per week.

We’re looking for a Staff Data Scientist to join our fast-paced, data-driven team. You will be a thought partner to senior leadership and shape the way we use economics and data science to drive long-term value and influence our product and monetization strategy. You’ll play a key role in understanding usage patterns in our platform via funnel analysis, causal analytics, and more to improve activation, engagement, and prevent churn.

The ideal candidate will work at the intersection of data, economics, and strategy to drive high-impact decisions across pricing, growth, and product monetization. You’ll apply your expertise in causal inference, econometrics, and behavioral analysis to answer some of the most critical questions in our business.

This is a hands-on IC role with outsized ownership, ideal for someone who thrives on solving ambiguous problems, building clean data narratives, and driving organizations toward better decisions with data.

• 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, Engineering, Operations teams, and Executives 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

• Help build and evolve our analytical foundation, including event instrumentation, metric frameworks, and scalable self-serve analytics tools

• Mentor other analysts and raise the bar for data storytelling, analytical rigor, and stakeholder influence across the org

• Frame ambiguous business problems into well-scoped analytical or modeling projects, especially those with strategic or monetization impact

• Apply advanced statistical and econometric techniques (causal inference, time-series forecasting, survival analysis, Bayesian inference) to analyze business problems

• Create compelling data narratives that drive senior-level decisions about product, pricing, growth, and retention

• Set standards and best practices for KPIs, metrics, and experimentation across the company

• Foster a culture of data-driven decision making through mentorship and skills development, especially regarding analytical rigor and communication

• 6+ years of experience in data science, applied economics, or a related field, ideally in high-growth tech environments

• Proven ability to identify and measure causal business impacts using appropriate statistical techniques, especially in complex or observational settings

• Strong…