Data Scientist

Remarcable, Inc.; Vancouver; Hybrid; CAD 90,000 - 130,000; Full time

Benefits offered by this job

Hybrid work in Vancouver

RRSP Matching

Health Spending Account (HSA)

Wellness Spending Account (WSA)

Competitive PTO

Job summary

Remarcable, Inc. is seeking a Data Scientist to design and build a data lakehouse, bringing data from across the business into one place to power reporting, product intelligence, and actionable insights.

The role blends analyst, scientist, and developer work to shape data architecture, build models, and create dashboards that drive product and operations decisions.

This is a hybrid role with our Vancouver office and a fast-paced startup environment offering high impact and clear ownership.

Qualifications

• 3+ years of experience in a Data Scientist, Analytics, or similar role
• Strong SQL and Python skills with experience in data analysis and modeling
• Experience building dashboards and reporting
• Experience with modern data transformation tools (dbt)
• Experience deploying ML models and heuristic approaches to business problems
• Familiarity with AWS data/ML stack (Redshift, Athena, SageMaker, Bedrock) is a plus

Responsibilities

• Partner with Data Engineering to design data lakehouse layers and analytics architecture
• Translate business questions into analyses and communicate findings to stakeholders
• Analyze product, operations, and customer data to identify trends and opportunities
• Build models and heuristics to power in-platform intelligence and forecasting
• Develop analytics supporting company metrics (ARR, churn, NRR, product usage)
• Create customer-facing and internal reporting for stakeholders
• Design and validate experiments (A/B tests) to improve user experience and outcomes

Skills

SQL

Python (pandas/NumPy)

Data Visualization

Dashboards

AWS data stack

Machine Learning

Communication

Modeling

Big data

dbt

Tools

dbt

AWS Redshift

Athena

Glue

SageMaker

Bedrock

QuickSight

Looker

Tableau

Power BI

Job description

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

• 3+ 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 (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.

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.

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