Principal Data Scientist

Forward Financing

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

Posted 9/21/2026full-timeRemote • United StatesLead💰 $208,000 - $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 high-impact data science initiatives. Proficient in advanced statistical and machine learning techniques, with strong project management and communication skills to influence technical direction and mentor teams.

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

Model DevelopmentMachine LearningStatistical AnalysisData Science InitiativesModel DeploymentReal-Time ModelsDecisioning EnginesWorkflow OrchestrationCredit Risk AnalysisDeep Learning

Soft Skills

Critical ThinkingProblem SolvingMentoringInfluencingCommunication

Tools & Technologies

AWSSageMakerMetaflowSnowflakeDatabricksArizeTaktileTecton

Industry Keywords

FintechLendingFinancial ServicesUnderwritingModel Validation

Tech Stack

Tools & technologies

AWSCloudPythonSQL

About the role

Key responsibilities & impact

Set the technical vision for data science at Forward Financing
Drive the highest-impact and most ambiguous data science initiatives from concept to production
Shape the multi-year data science roadmap
Define how models are built and deployed across the organization
Serve as a trusted technical advisor to senior leadership
Lead design, development, and deployment of complex, high-stakes statistical and machine learning models
Lead end-to-end delivery 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 Portfolio Strategy, Engineering, Product, Underwriting, Sales, and Collections to identify opportunities and influence business strategy
Define and enforce standards for model development, validation, code quality, and documentation
Make organization-wide technical 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

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 executive presentations
Strong critical-thinking and problem-solving ability
Nice-to-have experience with cloud data warehouses such as Snowflake and Databricks, Arize, Metaflow, SageMaker, decision engines such as Taktile, and feature stores such as Tecton
Bachelor's degree in Financial/Applied Math, Operations Research, Economics, and/or Statistics; Master's/PhD is a plus
Authorization to work for any employer in the US
Must disclose whether future visa sponsorship will be required

Benefits

Comp & perks

Flexible work location: home, office, or combination of both
Flexible hours
Medical benefits
Dental benefits
Vision benefits
Commuter benefits
Flexible time-off policy
Paid parental leave
401k match for US employees
Wellness reimbursement
Volunteering days
Annual professional development budget
Charitable donation match
Virtual and in-person team events
Potential additional 12% annual bonus