Principal Data Scientist

Forward Financing

. Set the technical vision for data science at Forward Financing .

Posted 9/21/2026full-timeRemote • CanadaLead💰 CA$208,000 - CA$286,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and deploying credit risk models, particularly in fintech and financial services, while leading data science initiatives from conception to production. Proficient in advanced statistical and machine learning techniques, with a strong emphasis on communication and project management skills.

Highest-signal resume keywords

Credit Risk Model DevelopmentStatistical And Machine Learning TechniquesPython, SQL, And Git ExpertiseCloud Platform Deployment (AWS, SageMaker)Project Management And Communication Skills

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine Learning ModelsStatistical AnalysisGeneralized Linear ModelsGradient BoostingDeep LearningModel ValidationCode Quality StandardsReal-Time ModelsDecisioning EnginesProduction-Grade Machine Learning Pipelines

Soft Skills

Critical ThinkingProblem-SolvingMentoringInfluencing Technical DirectionCommunication Skills

Tools & Technologies

AWSSageMakerMetaflowSnowflakeDatabricksArizeTaktileTecton

Industry Keywords

FintechLendingFinancial ServicesData ScienceModel DevelopmentUnderwriting ModelsPortfolio Strategy

Tech Stack

Tools & technologies

AWSCloudPythonSQL

About the role

Key responsibilities & impact

Set the technical vision for data science at Forward Financing
Shape the multi-year data science roadmap
Lead design, development, and deployment of complex, high-stakes statistical and machine learning models
Drive flagship data science initiatives from problem framing and model design through deployment, monitoring, and iteration
Lead technical strategy and architecture for the modeling ecosystem, including credit risk, pricing, and loss forecasting
Partner with senior leaders across Portfolio Strategy, Engineering, Product, Underwriting, Sales, and Collections
Identify high-value opportunities and influence business strategy with data
Define and enforce organization-wide standards for model development, validation, code quality, and documentation
Serve as technical authority on design decisions
Mentor data scientists at all levels, including senior and lead team members
Communicate technical concepts, tradeoffs, and business implications to executives and non-technical stakeholders
Represent data science in strategic planning
Architect and evolve production machine learning pipelines and monitoring frameworks
Ensure models are reliable, scalable, and continuously improving

Requirements

What you’ll need

Deep experience building and deploying credit risk models, especially underwriting models, in fintech, lending, or financial services
10+ years of hands-on model development and deployment experience
Advanced statistical and machine learning techniques, including generalized linear models, gradient boosting, and deep learning
Proven track record leading high-impact data science initiatives from ambiguity to production with demonstrated business results
Experience with real-time models, decisioning engines, and production-grade machine learning pipelines preferred
Expert in Python, SQL, and Git
Experience designing and deploying models within a cloud platform, such as AWS or SageMaker, including architectural decision-making
Experience with workflow orchestration tools, such as Metaflow, preferred
Strong foundation in statistics and machine learning
Ability to influence technical direction across teams and mentor senior technical talent
Excellent project management and communication skills, including presenting to executive audiences
Strong critical thinking and problem-solving ability
Experience with cloud data warehouses such as Snowflake and Databricks; Arize; Metaflow; SageMaker; decision engines such as Taktile; and feature stores such as Tecton is nice to have
Bachelor's degree in Financial/Applied Math, Operations Research, Economics, and/or Statistics
Authorization to work for any employer in Canada
Must not require sponsorship to work in Canada

Benefits

Comp & perks

Flexible work arrangements: employees may work from home, in the office, or a combination of both
Flexible hours
Medical insurance
Dental insurance
Vision insurance
Flexible time-off policy
Paid parental leave
RRSP match
Wellness reimbursement
Volunteering days
Annual professional development budget
Charitable donation match
Virtual and in-person team events
Potential additional 12% annual bonus