Data Scientist

Job summary

You will partner with Data Engineering to design the data lakehouse and build analytical layers to support internal and customer-facing reporting. Additionally, you will develop machine learning models and heuristics to drive product intelligence and business decision-making.

Job details

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. #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.

What you’ll do

You will partner with Data Engineering to design the data lakehouse and build analytical layers to support internal and customer-facing reporting. Additionally, you will develop machine learning models and heuristics to drive product intelligence and business decision-making.

Requirements

The role requires 3+ years of experience in a data science or analytics role with strong proficiency in SQL and Python. Candidates should have experience with modern data transformation tools and building practical machine learning models to solve business problems.

Benefits

• RRSP Matching Program • Health Spending Account • Wellness Spending Account • Competitive PTO

Listed skills

• Data visualization · Preferred
• SQL · Preferred
• Machine learning · Preferred
• Amazon Web Services · Preferred
• Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• SQL
• Python
• Pandas
• NumPy
• Data Modeling
• Machine Learning
• Data Engineering
• AWS
• Redshift
• Athena
• Glue
• SageMaker
• Bedrock
• dbt
• Data Visualization
• A/B Testing
• Internal Reporting
• AWS SageMaker
• Resourcefulness
• Business Problems
• Workflow Management
• Business Decisions
• Training Datasets
• Warehouse Operations
• Data Lakehouse
• Accounting
• Artificial Intelligence
• Amazon Web Services
• Amazon S3
• Analytics
• Dashboard
• Decision Making
• Communication
• Procurement
• Data Architecture
• Data Infrastructure
• Data Transformation
• Core Product
• Forecasting
• Python (Programming Language)
• NumPy (Python Package)
• Operations
• Performance Tuning
• Purchasing
• Recommender Systems
• Power BI
• Phishing
• SQL (Programming Language)
• Tableau (Business Intelligence Software)
• Tool Management

Job areas

• Data & Analytics
• Software
• Technology
• Engineering
• Construction
• Data Scientist
• Systems Analysts
• Data Scientists