Data Scientist
At a glance
Mid-level Data Science role at Remarcable, Inc. Vancouver · full-time · CA$150,000–CA$180,000 base.
dataroles summary, based on the employer's posting.
What you'll do
- Shape the lakehouse’s analytical layers with data engineering, organizing business data for reporting and product insights
- Turn open-ended business questions into analysis, then explain the results to technical and non-technical partners
- Study product, operations and customer activity to find patterns and anomalies that guide decisions
- Develop practical models for search, recommendations and forecasting, plus datasets and evaluation for AI and ML workflows
- Maintain company metrics, reporting and product experiments, including measures such as churn, usage and return on investment
What you bring
- At least five years in data science, analytics or a closely related role
- Strong SQL skills, including complex queries, window functions and query performance tuning
- Proficiency in Python with pandas and NumPy, plus experience creating dashboards or reporting
- You have built, tested and deployed practical machine-learning or heuristic models in production
- Experience with dbt or another modern data transformation tool
Who this fits
This mid-level role suits someone comfortable moving between analysis, modeling and development, and adapting in a startup setting. It is hybrid in Vancouver, with one work-from-home day.
From the employer
Overview
Remarcable is purpose-built for trade contractors, helping them manage procurement, tools, and warehouse operations with unmatched visibility and control. As we scale across North America, data is at the core of how we deliver on that promise.
As our Data Scientist, you'll partner closely with Data Engineering to design and build out our data lakehouse, bringing data from across the business into one place to power in-platform and internal reporting, sharpen Remarcable's product intelligence, and surface the trends and next-step recommendations that help contractors and our own teams make better decisions.
This is a high-ownership role for someone who's comfortable wearing multiple hats (analyst, scientist, developer) to shape data architecture and build out reporting, models, and insights that drive action and decision-making.
What You’ll Do
Partner with Data Engineering to design the lakehouse's semantic and analytical layers (on top of AWS S3, Redshift, Athena, Glue)
Translate ambiguous business questions into clear analyses, and communicate findings to technical and non-technical stakeholder
Analyze product, operations, and customer usage data to identify trends, anomalies, and opportunities that inform product and business decisions
Build models and heuristics that power Remarcable Intelligence (e.g. smart search, recommendation engine, forecasting)
Build out AI/ML data infrastructure - feature engineering, training datasets, and model evaluation - supporting SageMaker and Bedrock workflows
Develop and maintain core analytics supporting company metrics (ARR, churn, NRR, product usage, ROI)
Create customer-facing and internal reporting for customers and internal teams
Design and validate product experiments (A/B tests and other measurement methodologies) to drive data-informed decisions that improve user experience and business outcomes
Who You Are
5+ years of experience in a Data Scientist, Analytics, or similar role
Someone who thrives in a startup - adaptable, resourceful, and motivated by impact.
Strong SQL skills: complex queries, window functions, performance tuning
Proficiency in Python (pandas, NumPy)
Experience building dashboards/reporting (e.g., QuickSight, Looker, Tableau, Power BI, or custom-built reporting)
Experience with modern data transformation tools (e.g., dbt).
Experience building, validating, and deploying practical ML and heuristic models to solve business problems in a production setting (e.g. recommendation, trend analysis, scoring).
Bonus: experience with AWS data/ML stack (Redshift, Athena, SageMaker, Bedrock), and/or building recommendation or "next best action" style features
Why join us?
High Impact: Join a builder-led team where your work directly shapes the core product used by thousands.
Culture: Hybrid work environment in our Vancouver office (1 WFH day).
Retirement: RRSP Matching Program (50% match on the first 6% of your contribution).
Care: Health Spending Account (HSA) and Wellness Spending Account (WSA) administered via RBC.
Competitive PTO
Who we are
Remarcable is a cloud based platform that helps electrical contractors and distributors streamline purchasing processes to save time and money.
Dedicated to the Electrical Contractor Industry, Remarcable provides cloud-based Procurement & Tool Management Software nationwide. With multiple workflows, two applications in one software, and direct contractor accounting integrations, Remarcable significantly, and efficiently, increases communication, streamlines workflows, and provides visibility for all users.
Our team is composed of contractor and distribution experts located coast to coast. Through collaborations with industry leaders, we've gained insight into the struggles they face. Together, we believe in providing a solution that brings efficiency, visibility, and better communication to streamline the relationship between the contractor and distributor partners.
Our Mission
To advance the adoption of technology in the construction industry and bring better efficiency, visibility, and communication to our customers.
#ZR
Please be aware of potential phishing scams. Remarcable will never advance job applicants money or ask them to send money (via Venmo, Zelle, Paypal etc.) to preferred vendors. If you are concerned about the application process, please contact Remarcable directly at (216)770-3322.
Remarcable is not associated with info-remarcable.com. For information about applying for a position with Remarcable, please reference remarcable.com.
Data Science work from LinkedIn, X, Reddit and Upwork, in one list.
Each morning you get everything that fits, strongest first.
Data Science
Find me workBy the team behind dataroles.