1

Data Science Manager Jobs in Toronto, ON (NOW HIRING)

Credit Risk Expert & Strategic Builder We are looking for a hands-on, data-obsessed Data Science Manager, Risk to build and operationalize the models, data pipelines, and analytical frameworks that ...

Title and Summary Director, Data Science Overview The Security Solutions Data Science team is ... managing fraud and risk, enhancing cybersecurity, and improving the digital payments experience.

What You'll Be Doing The Manager, Data Science is responsible for providing analytics support to Business Lines and Finance team. This involves working with multiple stakeholders on data analysis ...

What You'll Be Doing The Manager, Data Science is responsible for providing analytics support to Business Lines and Finance team. This involves working with multiple stakeholders on data analysis ...

... managing data scientists or ML engineers * Proven track record building and deploying ML models in production , particularly in personalization, recommendation systems, or predictive modeling * Deep ...

... managing data scientists or ML engineers * Proven track record building and deploying ML models in production , particularly in personalization, recommendation systems, or predictive modeling * Deep ...

... managing fraud and risk, enhancing cybersecurity, and improving the digital payments experience. Within this space, the Identity Data Science portfolio plays an important role in advancing ...

Provide statistical expertise and develop data science solutions to Pharma technical operations ... Problem-Solving and Project Management: Strong analytical and problem-solving skills, ability to ...

Data Scientist

Woodbridge, ON

CA$85K - CA$115K/yr

... Science and other key stakeholders in bringing actionable data driven solutions to 407 ETR. This job involves model design, data management, data queries, and providing input into programs and ...

Data Scientist

Toronto, ON

CA$68K - CA$100K/yr

Ability to work collaboratively in a team environment and manage multiple priorities. * Experience: 2-4 years of experience in data science and Microsoft technologies. This role represents an ...

... Fraud Data Science team. In this role, you'll build and improve the models that power Stripe's fraud detection and loss management systems. You'll work closely with Fraud Engineering and Risk ...

How you'll shape Data Science at Achievers: * Work with a team of passionate data scientists on a ... Work with Product Managers and Development teams to develop, deploy, and monitor Machine Learning ...

Follow advancements in data science, machine learning, and healthcare analytics Qualifications ... Flexible Time Off - Autonomy to manage your schedule and work-life balance. * Health, Welfare and ...

The Mastercard Security Solutions Data Science team is seeking a Director of Data Science to lead ... Strong stakeholder management skills, with proven ability to work effectively across Product and ...

About the team Our Data Science team partners deeply with teams across Stripe to ensure that our ... key outcomes, managing liquidity, and quantifying risk exposure), how our go-to-market motions ...

next page

Showing results 1-20

Data Science Manager information

See Toronto, ON salary details

$76.8K

$146K

$197.5K

How much do data science manager jobs pay per year?

As of Aug 13, 2026, the average yearly pay for data science manager in Toronto, ON is $145,991.00, according to ZipRecruiter salary data. Most workers in this role earn between $116,429.00 and $174,644.00 per year, depending on experience, location, and employer.

What does a data science manager do?

As a Data Science Manager, your daily responsibilities typically include overseeing a team of data scientists and analysts, setting project priorities, and ensuring the timely delivery of data-driven solutions. You will often collaborate with cross-functional teams, such as engineering, product, and business stakeholders, to define problems, scope solutions, and communicate analytical insights. Your role also involves mentoring team members, reviewing code and analysis, and driving best practices in data science methodologies. This position requires balancing technical project oversight with team leadership and strategic business alignment.

What is a data science manager?

A Data Science Manager leads a team of data scientists to develop and implement data-driven solutions for business challenges. They oversee project timelines, ensure the quality of data analysis, and collaborate with cross-functional teams to drive decision-making. In addition to technical expertise, they require strong leadership, communication, and strategic thinking skills. Their role bridges the gap between data science initiatives and business objectives, ensuring the team's work aligns with company goals.

What is the role of a data science manager?

A data science manager oversees data science teams, guiding project priorities, setting strategic goals, and ensuring the effective use of data analysis and modeling techniques. They coordinate between technical staff and business stakeholders, often requiring skills in leadership, communication, and familiarity with tools like Python, R, or SQL. Their responsibilities include managing workflows, mentoring team members, and ensuring timely delivery of data-driven solutions.

What skills and qualifications are needed to be a data science manager?

To thrive as a Data Science Manager, you need strong analytical skills, experience in machine learning and data analytics, and a background in statistics or computer science, often supported by an advanced degree. Familiarity with tools like Python, R, SQL, cloud platforms, and experience managing data science projects are highly valued, and certifications such as Certified Analytics Professional (CAP) can be advantageous. Excellent leadership, project management, and communication skills are crucial for guiding teams and translating technical findings for stakeholders. These abilities ensure effective team performance, successful project delivery, and the alignment of data science initiatives with organizational goals.

What are the most commonly searched types of Data Science jobs in Toronto, ON? The most popular types of Data Science jobs in Toronto, ON are:
What are popular job titles related to Data Science Manager jobs in Toronto, ON? For Data Science Manager jobs in Toronto, ON, the most frequently searched job titles are:
What job categories do people searching Data Science Manager jobs in Toronto, ON look for? The top searched job categories for Data Science Manager jobs in Toronto, ON are:
What cities near Toronto, ON are hiring for Data Science Manager jobs? Cities near Toronto, ON with the most Data Science Manager job openings:
Infographic showing various Data Science Manager job openings in Toronto, ON as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 20% Part Time, and 1% Contract. Highlights an 93% Physical, 3% Hybrid, and 4% Remote job distribution, with an average salary of $145,991 per year, or $70.2 per hour.

Data Science Manager, Risk

Fig

Toronto, ON • On-site

Full-time

Medical, Dental, Vision, Retirement

Posted 7 days ago


Job description

About Fig

Fig is an award-winning, high-growth Canadian FinTech modernizing the world of consumer credit. We provide simple, accessible and fully digital personal loans, removing the complexity and delays of traditional lending to better serve Canadians.

Since launching in 2023, Fig has quickly built a strong reputation for innovation and customer trust. We have been named Consumer Lender of the Year by the Canadian Lenders Association and FinTech Startup of the Year by the FinTech Breakthrough Awards, and we are consistently recognized among Canada's Best Workplaces. Our commitment to customers is reflected in our 4.8 out of 5 Trustpilot rating.

Backed by Fairstone Bank of Canada and Ontario Teachers' Pension Plan, Fig combines deep lending expertise with the agility of a startup. This foundation allows us to effectively meet the evolving credit needs of Canadians across a wide range of financial backgrounds. 

The Role: Credit Risk Expert & Strategic Builder

We are looking for a hands-on, data-obsessed Data Science Manager, Risk to build and operationalize the models, data pipelines, and analytical frameworks that power our lending decisions. Reporting to the Director of Credit Risk, you will play a key role in advancing our credit risk capabilities through machine learning, data engineering, model governance, and data-driven experimentation. While this role does not include people management responsibilities in the short term, you will provide technical leadership by driving cross-functional initiatives, mentoring junior analysts, and championing best practices in data science and risk modeling.

You'll join an experienced team focused on Getting Stuff Done (#GSD), where curiosity, scientific rigor, and continuous innovation drive every decision. You'll work across the full model lifecycle from developing and deploying models to monitoring, governing, and continuously improving their performance. You should be comfortable navigating ambiguity, solving complex analytical problems, and translating insights into scalable, production-ready solutions.

This is an exciting opportunity to work across multiple data science disciplines, including credit risk model development, alternative labeling strategies, reject inference, model validation and quality assurance, feature engineering, model monitoring, production decisioning, and credit risk data engineering. You'll design robust data pipelines, improve model performance and governance, automate analytical workflows, and partner closely with Credit Strategy, Product, Finance, Growth and Engineering to deliver scalable, data-driven lending solutions. This is a newly created role, which means you'll have the opportunity to help shape the mandate, build core processes, and make a visible impact as Fig continues to grow.

Culture matters deeply to us. You'll have the support of experienced colleagues across the organization who are passionate about solving challenging problems together. We're looking for someone who combines strong technical expertise with curiosity, collaborates effectively across teams, and thrives in an environment that values transparency, accountability, and continuous improvement.

What You'll Do
  • Develop Next-Generation Credit Models: Build, enhance, and deploy machine learning models for underwriting, reject inference, alternative labeling, and other credit risk applications.

  • Drive Model Governance & Quality: Partner with model validation to ensure robust model governance through comprehensive documentation, performance monitoring, stability analysis, diagnostics, and ongoing model enhancements.

  • Advance Credit Strategy: Partner with the Credit Risk team to evaluate underwriting policies, optimize risk segmentation, and translate model insights into data-driven credit strategies.

  • Enable Scalable Credit Analytics: Develop analytical datasets, reusable feature frameworks, and scalable workflows that accelerate model development, portfolio monitoring, and strategic decision-making.

  • Drive Statistical Experimentation: Design and evaluate statistically rigorous experiments to assess new models, features, and credit strategies, using data to quantify business impact and optimize decision-making.

  • Productionize Decisioning: Translate analytical solutions into scalable production workflows, partnering with Engineering to automate credit decisioning and improve operational efficiency.

  • Build AI-Powered Solutions: Develop and deploy AI-powered solutions across credit risk and fraud to enhance decision-making, strengthen fraud detection, and improve operational efficiency.

  • Collaborate Across Teams: Partner closely with Credit Strategy, Product, Growth, Finance, Engineering, and Data teams to deliver high-quality, data-driven solutions that balance portfolio growth, risk, and customer experience.

What You'll Bring
  • Subject Matter Experience: 4 or more years of experience in Credit Risk management, modeling and/or related data analysis in a financial services, FinTech, lending and/or technology company.

  • Technical Mastery: Strong proficiency in Python and SQL is required.

  • Analytical Depth: Working knowledge of regression analysis, decision trees, loss forecasting, and statistical design of experiments.

  • Exceptional Communication Skills: The ability to translate complex data into clear, professional narratives for Senior Management.

  • Startup DNA: You thrive in fast-paced environments with limited structure and have a shared sense of purpose to "Get Stuff Done" (#GSD).

Why Fig?
  • Make Your Mark: This is a rare chance to help directly steward a high-impact FinTech in Canada at an exciting stage of its growth and maturity.

  • The Culture: Work in a team that values impact, accountability, curiosity, and building strong, collaborative relationships.

  • Hybrid Work Environment: Balance of remote and in-office (currently one day a week in Toronto), without sacrificing the high-energy collaboration.

  • Competitive compensation ($95,000 - $120,000 base + bonus).

  • Retirement savings program with employer matching.

  • Comprehensive medical, dental, and vision group insurance, as well as health and wellness spending accounts.

  • Generous time off to help you recharge.

  • Parental top-up to support your growing family.

  • Continuing education stipend to support your professional development.

Our commitment to diversity, equity and inclusion

We are an equal opportunity employer and are committed to diversity at our company. We do not discriminate on the basis of race, religion, culture, sexual orientation, gender identity and physical ability.

Diversity of backgrounds, perspectives, and experience is fundamental to our business. We believe in fostering an environment where team members of all backgrounds can feel comfortable bringing their whole selves to work every day. We aim to ensure all of our employees work in an environment that makes them feel valued, heard, and supported while they strive towards career pursuits and their personal and professional growth.

We are committed to providing accommodations for all candidates that require them and in all aspects of the recruitment, selection, and/or assessment process. If you are selected to participate in any part of the selection and/or assessment process, please inform us of any accommodation(s) that you may require.

AI Disclosure

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

We're flattered that you'd like to join our team, but only applicants selected to proceed in the hiring process will be contacted.

$95,000 - $120,000 a year
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
apply for this job