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Vancouver, BC (Hybrid) · Vancouver, British Columbia, Canada
Live, first seen by us 49 days agoLocation type: HybridFrom the employer’s posting
Employment type: Full-timeFrom the employer’s posting
Department: EngineeringFrom the employer’s posting
Design the lakehouse's semantic and analytical layers on AWS
Build models and heuristics for smart search, recommendations and forecasting
Build AI/ML data infrastructure for features, training data and evaluation
Maintain core metrics such as ARR, churn, NRR and product usage
Design and validate A/B tests and other product experiments
Partner with Data Engineering to design the lakehouse's semantic and analytical layers
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
Develop and maintain core analytics supporting company metrics (ARR, churn, NRR, product usage, ROI)
Design and validate product experiments (A/B tests and other measurement methodologies)
5+ years of experience in a Data Scientist, Analytics, or similar role
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).
Remarcable is a cloud based platform that helps electrical contractors and distributors streamline purchasing processes to save time and money.
In the employer’s words · Read in context · Company website ↗
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Day 49
Similar jobs usually come down between day 7 and day 55.
From 9,971 similar postings that came down. Coming down is not always a hire.
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- 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)
- 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)
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
- 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?
- 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).
- 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).
- 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)
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We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
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.
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
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
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
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.
To advance the adoption of technology in the construction industry and bring better efficiency, visibility, and communication to our customers.
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Remarcable is not associated with info-remarcable.com. For information about applying for a position with Remarcable, please reference remarcable.com.
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Vancouver, British Columbia, Canada
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).
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