About the role

Data Scientist at LawDepot optimizing the Checkout experience through data-driven decisions. Involves statistical analysis, experiment design, and collaboration to enhance revenue growth.

Responsibilities

Explore and analyze both experimental data and day to day user data to understand performance across the Checkout experience
Own end to end analytical initiatives, identifying and executing on revenue opportunities informed by past experimentation, competitive analysis, and market trends
Design, evaluate, and monitor controlled experiments, identifying follow up optimization opportunities
Create baseline models and establish experiment metrics to measure uplift, validate hypotheses, and inform revenue growth decisions
Translate behavioural insights into clear business recommendations tied to subscription valuation and monetization
Develop SQL queries and Python code for data extraction, analysis, and automation
Design dashboards that enable self-service reporting and support decision-making
Build clear, actionable data visualizations that make insights accessible to stakeholders
Apply appropriate statistical and modeling techniques based on the problem and available data
Create and initiate monetization projects based on learnings from past initiatives, competitive analysis, and market trends
Contribute to improving data tracking, event quality, and attribution logic over time
Collaborate with analysts, developers, and product stakeholders to ensure accurate tracking and measurement
Present findings in weekly team meetings and contribute to prioritization decisions

Post secondary education in Data Science, Business, Finance, Economics, Mathematics, Statistics, Computer Science, or a related field
Solid foundation in statistical analysis, including hypothesis testing and interpreting experimental results
Ability to execute well-scoped analytical tasks and models under minimal guidance, contributing accurate and timely insights to business problems
Proficiency in SQL, including writing efficient queries with joins, aggregations, and filtering logic
Familiarity with Python for data analysis and visualization (ex. pandas, Matplotlib)
Proficiency in Microsoft Excel, including Pivot Tables, formulas, and data visualization
Strong communication skills and ability to explain complex analysis clearly
Proactive mindset with a willingness to take ownership
Curiosity and a natural tendency to dig deeper into unexpected results

Comprehensive health and dental benefits, plus an additional Health Care Spending Account
Great work life balance (37.5 hour work weeks, flexible schedules, ability to bank hours)
Three weeks paid vacation, plus bonus personal days
Continuous learning opportunities, including LinkedIn Learning subscriptions and training budgets
Company share plan
Free catered lunches for the entire office
Monthly social events for team members to enjoy (think axe throwing, rock climbing, board games, food trucks, trivia contests, and charitable activities)
Casual work environment
Personal offices for focused work and to have your individual space (plus collaborative workspaces for when you want to meet with the team)
Free and easily accessible parking