Data Product Analyst (Data Science)

Role Overview

The Data Product Analyst will serve as a critical bridge between business stakeholders, data science and analytics teams, and data management groups. This role combines strong data analysis and data science capabilities with core business analysis skills to ensure that data is effectively leveraged to inform strategic decision making, improve processes, and influence solution design.

What You Will Do

The Data Product Analyst will frame business problems as analytical and modeling questions, apply statistical and machine learning methods to answer them, and translate the results into clear, actionable recommendations.

Why It Might Be a Fit

The ideal candidate will have a strong understanding of data stewardship principles, including data quality, lineage, metadata management, and responsible data use, and the ability to adapt these skills across a wide range of use cases.

Requirements

• Bachelor’s degree in information systems, business analysis, statistics, computer science, data science, or related fields
• 2-5 years of experience in data analysis, data science, business analysis, product analytics, or similar roles
• Skilled at requirements elicitation, process mapping, and translating business needs into technical specifications, user stories, acceptance criteria, and high-quality documentation
• Strong understanding of data stewardship principles, including data quality, lineage, metadata management, and responsible data use
• Comfortable connecting data across multiple systems and enriching datasets to enable new insights for business stakeholders
• Excellent communication, with the ability to tailor messages for both technical teams (engineering, data science) and business stakeholders
• Champions a consumer-first mindset, grounding product, data, and insights decisions in a deep understanding of consumer behaviors and needs
• Collaborative mindset with the ability to influence without authority, navigate ambiguity, and drive alignment across cross-functional teams
• Naturally curious and a strong critical thinker, with a passion for exploring new data sources and solving problems with incomplete, messy, or evolving datasets
• Strong analytical toolkit leveraging SQL, Python (e.g., pandas, NumPy, scikit-learn), and BI tools (e.g., Power BI, Tableau) to explore, transform, model, and validate complex datasets
• Solid grounding in statistics, model evaluation, and validation practices, with working knowledge of machine learning methods (e.g., regression, tree-based models, time-series forecasting) and exposure to generative AI and LLM-based tooling
• Working knowledge of data modeling, ETL/ELT pipelines, and cloud data platforms (e.g., Snowflake, Databricks, AWS) to support reliable data products, along with Git-based version control
• Proven ability to work effectively in cross-functional environments and support the delivery of data products, including analytical and ML-driven products, that serve multiple stakeholders

Benefits

• Opportunity for advancement and career progression
• Competitive compensation
• Successful referral program
• The opportunity to work with one of Canada’s 50 Best Managed Companies
• Satisfaction of working for a reputable company
• A flexible, dynamic, and diverse workplace

Tagged as: Data Analysis, Forecasting, Power BI, Python, Snowflake