Senior Data Scientist

At Momentum Financial Services Group, we help people move forward by reimagining how money works for those who need it most. With more than 40 years of experience, we’re the team behind Money Mart—Canada’s largest non-bank branch network—and a leader in financial solutions for underserved communities.

From short-term loans to money transfers and prepaid cards, we power the products, technology, and operations that connect over a million customers a year to the money they need, when they need it.

At MFSG, we come together across teams and departments to create something bigger than ourselves: solutions that remove barriers and give people access to money they might not get anywhere else. Whether you're solving problems, building systems, or shaping strategy, your work fuels real support for real people.

• →Design, develop, validate, and implement predictive and prescriptive models that address emerging business needs and new initiatives. Continuously improve the overall modeling process, including feature selection and engineering, model development, validation, monitoring, and documentation, to enhance model performance, scalability, and efficiency. 
• →Lead the development, implementation, and ongoing enhancement of Customer Lifetime Value (CLV) models to support customer strategy and business decision-making. Partner with Product, Marketing, Finance, and other business teams to translate business needs into modeling solutions, establish performance tracking, monitor model effectiveness, and continuously refine methodologies as customer behavior and business priorities evolve. 
• →Partner with business stakeholders across various functions to understand business questions and provide data-driven insights through ad hoc analytics. Analyze complex datasets, identify meaningful patterns and opportunities, and translate analytical findings into actionable recommendations that support business decisions and strategies. 
• →Analyze large and complex financial datasets to extract meaningful patterns and features that improve model accuracy and business insights.
• →Ensure that models comply with industry regulations, internal policies, and audit requirements.
• →Monitor model performance over time and implement retraining or improvements as necessary.
• →Lead and support strategic data science initiatives such as portfolio optimization and customer behavior analysis, collaborating with partners across cheque cashing, marketing, cross-country operations, and card services to deliver data-driven solutions that improve risk management, business performance, and customer outcomes.

• Master’s degree with 5+ years, or PhD with 2+ years, of hands-on experience in data science, econometrics, statistics, financial economics, or a related quantitative field.
• Experience developing, validating, implementing, monitoring, and refining predictive models and analytical solutions, preferably within financial services.
• Strong knowledge of statistical and machine learning techniques, feature engineering, model performance monitoring, and working with large financial or customer datasets.
• Advanced proficiency in Python and SQL for data analysis, statistical modeling, and machine learning. 
• Strong knowledge of predictive modeling, regression, classification, forecasting, segmentation, and model evaluation techniques. 
• Experience with feature engineering, feature selection, model validation, performance monitoring, and model refinement. 
• Experience working with large-scale customer, transactional, and financial datasets. 
• Strong data visualization and analytical communication skills. 

• Bachelor’s degree in a quantitative STEM field such as Computer Science, Data Science, Statistics, Mathematics, Economics, Finance, Engineering, or related discipline. 

• Experience with Customer Lifetime Value (CLV), customer behavior, profitability, forecasting, or similar customer-level modeling.
• Experience with IFRS 9, credit risk, expected loss, or other financial models involving segmentation, forward-looking forecasts, and ongoing model monitoring is an asset.
• Experience with CLV methodologies, survival analysis, customer behavior modeling, or profitability/forecasting models. 
• Knowledge of IFRS 9, credit risk modeling, or other financial modeling frameworks. 
• Experience with cloud-based analytics and ML platforms (e.g., SnowFlake, Azure, Databricks). 
• Familiarity with MLOps, model deployment, automated monitoring, and improving end-to-end modeling processes. 

• Master’s or PhD in Data Science, Statistics, or a closely related quantitative field. 

Committed to Equal Opportunity:
MFSG is committed to accommodating applicants up to the point of undue hardship during the recruitment, assessment and selection process. If you are selected for an interview, please notify MFSG if you require accommodation in respect of the materials or procedures used at any time during this process. If you require accommodation, MFSG will work with you to determine how to meet your needs.