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Momentum Financial Services Group

Senior Data Scientist

Toronto, ON, Canada

Please note: The salary range for this position is between C$ 110,000 to C$ 125,000.

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Job details

Pay: Please note: The salary range for this position is between C$ 110,000 to C$ 125,000.
Experience: 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.
Posting language: English
Posted: Oct 5, 2026

Original job description

Who We Are

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.

We’ve Got You Covered

Compensation Philosophy: Our strategy is simple - we aim to match the market. We regularly review industry standards to ensure our total rewards package is competitive and fair. This commitment helps us attract and retain talented individuals who share our purpose.

Discretionary Annual Bonus: Enjoy the opportunity for a discretionary bonus based on individual performance and company success.

Comprehensive Benefits: Our benefits include health and dental plans with 100% of the premiums covered. We also offer an Employee Assistance Program to support your mental well-being and provide resources for personal challenges.

Retirement Plans: Plan for your future with our robust retirement savings options, ensuring you’re set for the long haul.

Hybrid Work Environment: Experience the best of both worlds with our hybrid work model, allowing you to balance remote work with in-office. When you're at our corporate head office, enjoy a relaxed and collaborative environment featuring breakout rooms for brainstorming and unwinding, plus a variety of snacks to keep you energized throughout the day.

Perks and Rewards: Enjoy reimbursement for tuition assistance and professional development, discounts through Perkopolis and participate in our rewards and recognition programs to celebrate your contributions.

The Job: Senior Data Scientist

This individual will be the key person for consulting with the business to identify opportunities and implement advanced analytics and data science solutions that support business needs and new initiatives. Reporting directly to the Senior Director of Data Science, the Senior Data Scientist will be the subject matter expert for predictive analytics and machine learning, working closely with various business, product, marketing and technology teams to develop and implement models that drive measurable business value. In addition to developing data science solutions, the individual will have opportunities to work closely with business leaders in identifying new use cases, presenting

What You’ll Do

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.

What You’ll Bring to the Table

Required

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.

Desired

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.

Education + Professional Accreditations

Required

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

Desired

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

Please note: The salary range for this position is between C$ 110,000 to C$ 125,000.

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.

About MFSG – Our Commitment to Responsible Innovation

At MFSG, we are committed to building innovative solutions grounded in ethical, transparent, and responsible use of data and technology. Aligned with the principles outlined in Canada’s Artificial Intelligence and Data Act (AIDA), we take a proactive approach to ensuring that any AI or data-driven systems we use are safe, fair, and accountable.

This posting is for a current position within our organization, offering the opportunity to contribute to meaningful, responsible innovation that supports our employees, clients, and communities.

We prioritize strong data governance, clear communication around how systems work, and safeguards that reduce risks and protect individuals. Our focus is on developing tools and processes that promote equity, reliability, and trust, supported by ongoing monitoring and continuous improvement.

Joining MFSG means contributing to a future-focused organization that values both innovation and integrity, where your work helps shape solutions that responsibly support our employees, clients, and communities.

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More about this job

Responsibilities

The Senior Data Scientist will design, develop, and implement predictive and prescriptive models to address business needs and drive measurable value. They will collaborate with cross-functional teams to translate business requirements into analytical solutions and provide data-driven insights.

Requirements

Candidates must hold a Master's degree with 5+ years or a PhD with 2+ years of hands-on experience in a quantitative field. Proficiency in Python, SQL, and advanced statistical modeling techniques is required, preferably within the financial services sector.

Skills

Python
SQL
Predictive modeling
Machine learning
Statistical analysis
Feature engineering
Data visualization
Customer lifetime value
Econometrics
Financial modeling
Model validation
Performance monitoring
Data science
Risk management
Forecasting
Segmentation

Benefits

Health insurance
Dental insurance
Employee assistance program
Retirement savings plan
Tuition assistance
Professional development
Discretionary annual bonus
Discounts through Perkopolis

Visa sponsorship

Not detected in the job text

Keywords

Data Science
Python
SQL
Predictive Analytics
Machine Learning
Customer Lifetime Value
Financial Services
Econometrics
Statistics
Feature Engineering
Model Validation
Snowflake
Azure
Databricks
MLOps
IFRS 9
Credit Risk
Portfolio Optimization
Data Visualization
Regression
Classification
Forecasting
Survival Analysis
Data Governance
Quantitative Analysis
Business Intelligence
Strategy
Analytical Communication
Model Monitoring
Transactional Data

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