Data Scientist, Product Analytics

About Leap Tools

Leap Tools builds advanced interior décor technology used by customers in more than 80 countries. Its users include large enterprises such as Home Depot, regional retailers like Alexanian's, and many others. The company has been recognized by Deloitte multiple years in a row as one of the fastest-growing tech companies and is looking for driven people who want to help shape a major global technology business.

About the Product

The product helps shoppers visualize décor items in their own space before making a purchase. Whether someone is choosing kitchen tiles or a living room rug, the platform makes it easy to see how the item will look at home using a simple, accessible experience.

What You Will Do

• Apply statistical and analytical methods to solve important business problems using large, complex datasets.
• Partner with product managers and engineers to study user behavior, product engagement, and feature adoption in order to improve the product experience.
• Design, run, and assess A/B tests, then present the findings in a way that supports product improvements and helps customer-facing teams promote new features and products.
• Work with product managers to define key product metrics and create dashboards to track performance.
• Spot patterns and trends in data proactively to support product development, sales initiatives, and industry thought leadership in home décor.
• Use statistical modeling and machine learning for tasks such as forecasting trends and grouping customers into meaningful segments.
• Turn data into insights for individual customers so they can better understand user behavior and preferences for targeted marketing.

What We Are Looking For

• Strong practical experience in data preprocessing, cleaning, wrangling, feature engineering, analysis, and statistical modeling, with the ability to deliver polished insights for customers.
• Meticulous attention to detail and a strong commitment to quality.
• Excellent communication skills with the ability to explain complex results to non-technical audiences.
• Comfort interacting with customers and senior leaders.
• A technical foundation through a degree in statistics, mathematics, or a related technical discipline, or equivalent relevant work experience.
• Proficiency in SQL or another data querying language, plus at least one scripting language for analysis such as Python.

Tech Stack

The team works with Python libraries such as pandas, matplotlib, scikit, numpy, and scipy, along with Superset, Redshift, PostgreSQL, Django, and dbt.

Culture and Benefits

• Remote-first work setup that supports productivity from wherever you work best.
• Small, close-knit teams that encourage ownership and accountability.
• A strong focus on curiosity and attention to detail.
• A fast-moving environment with an emphasis on delivering on commitments quickly.
• Ability to work from anywhere in the world for up to 3 months.
• Parental leave support.
• Work-from-home stipend.
• Your birthday and the company’s birthday are both days off.

Hiring Process

• Submit a resume and complete a short questionnaire.
• Join a video call to review your abilities and complete a take-home assessment.
• Attend two follow-up video interviews.
• Meet one of the founders.
• Receive an offer.

Compensation and Additional Information

The Ontario-based compensation range is $80,000 to $110,000 per year, plus additional benefits. The company is open to candidates whose experience or compensation expectations fall outside the stated range and may tailor the role and pay accordingly.

This is an already open position on the team.

Leap Tools is an equal opportunity employer committed to an inclusive, equitable, and accessible workplace. Accommodation is available on request during the interview process.

The company uses AI tools in recruiting for support tasks such as resume screening, candidate sourcing, and administrative efficiency, but final hiring decisions are made by founders and senior leadership. AI is not used to make the final decision.

Candidates are encouraged to apply even if they do not match the role perfectly, as the company may create a new role with corresponding compensation for exceptional talent.