Back to jobs

Data Scientist

Vancouver, BC (Hybrid) · Vancouver, British Columbia, Canada

Live, first seen by us 49 days ago
Pay
Pay not listed
Work setting
Hybrid — work setting source
Location type: Hybrid
From the employer’s posting
Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting
Team
Engineering — team source
Department: Engineering
From the employer’s posting

What you’ll work on

Full 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

From the employer’s posting
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)

What you’ll bring

All qualifications

Core experience

  • 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.
Qualification wording
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).

About Remarcable

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 ↗

Apply at Remarcable

Posting record

Report an error
Status in our records
Live
First seen by us
Sep 16, 202649 days ago
Recorded sightings
31
Last seen by us
Nov 4, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 49

Similar jobs usually come down between day 7 and day 55.

From 9,988 similar postings that came down. Coming down is not always a hire.

Remarcable is hiring

1 open job

Open jobs by the week we first saw them, last 12 weeks.

Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • AWS
  • dbt
  • Looker
  • Power BI
  • Redshift
  • S3
  • SageMaker
  • Tableau
  • NumPy
  • pandas
Where the posting names them
- 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)

Your next step

Complete your application on jobs.ashbyhq.com. The employer’s form will show what is required.

Applying through Ashby

  • No account needed. “Autofill from resume” at the top of the form fills the key fields from your file.

Already applied? Track this application

About the role

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.

US government figures for data scientists

Median yearly pay, May 2025
$120,230
Expected change, 2025 to 2035
34.6% more jobsagainst 3.5% for all jobs

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.

Job description

View original posting ↗

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.

Source details

View original posting ↗

Source notes

Source excerpts

Selected passages from the saved posting. Check the full description for conditions and exceptions.

Pay

No pay amount identified in the saved description.

Location & working pattern

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).
Work authorization

No clear work-authorization passage found. Eligibility is unconfirmed.

Find answers in the posting

AI
How answers work

AI selects complete passages from this posting. Check them for conditions and exceptions.

Uses this posting and your question. No profile needed.