Data Scientist US - Remote Role

TRENT HOEK OUTDOORS LLC
United States
8 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
10 years minimum
Compensation
$208,000.0 - $286,000.0
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Amazon Web Services Cloud Database Cloud Engineering Software Quality Generalized Linear Model Monitoring of Systems Python (Programming Language) Machine Learning Rule Engine Standard Sql SQL Databases
+9 more
Computational Statistics Feature Store Snowflake Deep Learning Model Validation Git Xgboost Machine Learning Operations Databricks

Job description

Forward Financing is seeking a Principal Data Scientist to set the technical vision for data science and lead the organization’s highest-impact, most ambiguous initiatives from concept through production. As the most senior individual contributor on the data science team, this role will shape the multi-year data science roadmap, establish standards for model development and deployment, and serve as a trusted technical advisor to senior leadership.

The role combines deep technical execution with strategic business partnership, delivering advanced statistical and machine learning solutions across business domains, with particular focus on credit risk, pricing, and loss forecasting. You will work closely with Portfolio Strategy, Engineering, Product, Underwriting, Sales, and Collections while mentoring data scientists and influencing technical and business strategy.

Key Responsibilities

  • Lead the design, development, and deployment of complex, high-stakes statistical and machine learning models, particularly in ambiguous problem spaces.

  • Drive end-to-end delivery of 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 to shape the data science roadmap.

  • Identify high-value opportunities and use data science to influence business strategy.

  • Define and enforce organization-wide standards for model development, validation, code quality, and documentation.

  • Serve as the technical authority for data science 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., As part of its stated commitment to a streamlined and equitable hiring experience, Forward Financing uses AI tools to assist with candidate screening and assessment.

Requirements

  • Deep experience building and deploying credit risk models, particularly underwriting models, within fintech, lending, or financial services.

  • 10+ years of hands-on model development and deployment experience.

  • Advanced statistical and machine learning experience, including generalized linear models, gradient boosting, and deep learning.

  • Proven track record leading high-impact data science initiatives from ambiguous problem definition through production with demonstrated business results.

  • Expert proficiency in Python, SQL, and Git.

  • Experience designing and deploying models within cloud platforms such as AWS or SageMaker, including architectural decision-making.

  • Strong foundation in statistics and machine learning.

  • Demonstrated ability to influence technical direction across teams.

  • Demonstrated ability to mentor senior technical talent.

  • Excellent project management and communication skills.

  • Experience presenting to executive audiences.

  • Strong critical-thinking and problem-solving abilities.

  • Bachelor’s degree in Financial/Applied Math, Operations Research, Economics, Statistics, or a related field listed in the source requirements.

Preferred Qualifications

  • Experience with real-time models and decisioning engines.

  • Experience with production-grade machine learning pipelines.

  • Experience with workflow orchestration tools such as Metaflow.

  • Master’s or PhD degree.

  • Experience with cloud data warehouses such as Snowflake or Databricks.

  • Experience with Arize.

  • Experience with SageMaker.

  • Experience with decision engines such as Taktile.

  • Experience with feature stores such as Tecton.

Skills & Competencies

  • Principal-level Data Science

  • Statistical Modeling

  • Machine Learning

  • Credit Risk Modeling

  • Underwriting Models

  • Pricing and Loss Forecasting

  • Generalized Linear Models

  • Gradient Boosting

  • Deep Learning

  • Python

  • SQL

  • Git

  • AWS

  • SageMaker

  • Machine Learning Pipelines

  • Model Deployment

  • Model Monitoring

  • Model Validation

  • Cloud Architecture

  • Decision Engines, Education: Bachelor’s degree in Financial/Applied Math, Operations Research, Economics, Statistics, or a related field. Master’s or PhD is a plus.

Experience: 10+ years of hands-on experience developing and deploying models using advanced statistical and machine learning techniques, with deep experience in credit risk and underwriting models in fintech, lending, or financial services.

Work Arrangement & Schedule

  • Employment Type: Full-time

About the company

Forward Financing is a financial technology company headquartered in Boston, Massachusetts, with team members throughout the United States, Dominican Republic, and Canada. The company provides funding solutions to small businesses across America.

Since 2012, Forward has provided more than $4.8 billion in funding to more than 92,000 small businesses. The company describes itself as remote-first and focuses on investing in employees, technology, and customer experience.

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