DATA SCIENTIST

We are banking at another level.

Choosing BDC as your employer means working in a healthy, inclusive, and skilled workplace that puts forward the best conditions to bring together unique teams where employees are empowered to act. It also means being at the centre of ambitious economic and financial projects to see further and to do things differently, to fuel the success of Canadian entrepreneurs.

Choosing BDC as your employer also means:

• Flexible and competitive benefits, including an Employee Savings and Investment Plan where BDC matches part of your voluntary contributions, a Defined Benefit Pension Plan, a $750 wellness and health care spending account, to name a few   

• In addition to paid vacation each year, five personal days, sick days as necessary, and our offices are closed from December 25 to January 1

• A hybrid work model that truly balances work and personal life

• Opportunities for learning, training and development, and much more... 

Explore the BDC Way in our Culture Book

POSITION OVERVIEW

The Data Scientist is responsible for developing advanced analytics and machine learning solutions that drive data informed decision-making across the organization. This role focuses on transforming complex data into actionable insights through statistical modeling, predictive analytics, and experimentation, while partnering closely with business stakeholders, data engineers, and AI engineers. The Data Scientist plays a key role in bridging business problems with rigorous analytical solutions that are scalable, interpretable, and impactful.

CHALLENGES TO BE MET

• Analyze complex, large‑scale datasets to uncover insights, trends, and opportunities that support strategic and operational decisions.

• Design, develop, and validate statistical models and machine learning algorithms for predictive, descriptive, and prescriptive analytics use cases.

• Collaborate with business partners to frame analytical problems, define success metrics, and translate business questions into data science solutions.

• Build and maintain end-to-end data science workflows, from data exploration and feature engineering to model training and evaluation.

• Partner with data engineers and AI engineers to productionize models and ensure scalability, performance, and reliability.

• Conduct experiments (e.g., A/B testing, causal analysis) to measure impact and support evidence-based decision-making.

• Interpret and communicate analytical results clearly to both technical and non‑technical audiences through presentations, dashboards, and written documentation.

• Ensure data quality, reproducibility, and adherence to data governance, privacy, and ethical AI standards.

• Contribute to documentation, best practices, and knowledge sharing through internal wikis, playbooks, and analytics standards.

• Stay current with advances in data science, machine learning, and analytics techniques, and proactively propose improvements or new approaches.

WHAT WE ARE LOOKING FOR

Technical Proficiency:

• Strong programming skills in Python and SQL; experience with data manipulation and analysis libraries (e.g., pandas, NumPy, scikitlearn).

• Experience working with large datasets using Databricks notebooks and workflows. Understanding the advantages and limitations of distributed computing with Spark is essential.

• Use of Git and Azure Devops (or equivalent such as JIRA) to track development and project coordination. Proficiency in data visualization and storytelling using tools such as Power BI, Tableau, or equivalent libraries. Capacity to properly present prescriptive recommendations rather than descriptive observations is essential.

Data Science & Analytics Expertise:

• Solid foundation in statistics, probability, and machine learning techniques (e.g., regression, classification, clustering, time series).

• Experience with feature engineering, model evaluation, and model interpretability.

• Familiarity with experimentation frameworks and causal inference concepts is required.

Collaboration & Communication:

• Ability to translate complex analytical findings into clear, actionable insights.

• Strong stakeholder engagement skills, with the ability to challenge assumptions and influence decisions using data.

Experience:

• Minimum 3 years of experience in data science, advanced analytics, or a related role, with demonstrated impact on business outcomes.

Education

• Bachelor’s, Master’s, or PhD in Data Science, Statistics, Computer Science, Engineering, Mathematics, Economics, or a related quantitative field.

Proudly one of Canada’s Top 100 Employers and one of Canada’s Best Diversity Employers, we are committed to fostering a diverse, equitable, inclusive and accessible environment where all employees can thrive and feel empowered to bring their whole selves to work. If you require an accommodation to complete your application, please do not hesitate to contact us at [email protected].

While we appreciate all applications, we advise that only the candidates selected to participate in the recruitment process will be contacted.