Senior Data Scientist

One Park Financial (OPF) is a leading Financial Technology company dedicated to empowering small businesses by connecting them with a wide variety of flexible financing and funding options. Our mission is to provide entrepreneurs with the working capital they need to elevate their businesses to new heights. We foster a dynamic and inclusive company culture that emphasizes collaboration, innovation, and personal growth, with a team of passionate, driven individuals committed to making a difference.

About The Role

We are looking for a seasoned Senior Data Scientist to join our Analytics team to enable core business transformation. This role involves building and pressure-testing models and proposals that drive how we price, approve, and grow, with the statistical and analytical rigor to prove they work before they ship. You will own a production system end-to-end, helping operate and evolve our proprietary risk-based pricing engine, the application that powers our real-time offer decisioning. You will work closely with business stakeholders to understand problems and propose & implement AI/ML solutions, partnering with DevOps, Product, and Engineering to take models from notebook to production. You will lead A/B testing within the organization and design experiments to prove success.

Responsibilities

• Utilize advanced statistical and machine learning techniques to analyze large datasets and build new AI/ML models
• Develop and pressure-test pricing and credit proposals end-to-end, with the statistical and analytical rigor to prove they will work before they ship
• Conduct exploratory data analysis, feature engineering, and data preprocessing to solve business problems
• Own, operate, and enhance our proprietary risk-based pricing engine (a production Python application), including its models, business logic, deployment, and monitoring
• Facilitate the deployment and monitoring of models for real-time and batch processing
• Own strong model governance: clear documentation and versioning, ongoing monitoring for drift and degradation, regular validation, and a defensible audit trail across the model lifecycle
• Partner with DevOps, Product, and Engineering teams to ship models and features to production, owning the rollout from staging to production, including CI/CD, monitoring, and rollback
• Perform model evaluation and validation on a regular basis to ensure robust performance
• Engineer A/B tests with scientific rigor. Gather test data and validate results to present to business stakeholders
• Use modern AI and LLM tooling to speed up your own work, from EDA and feature engineering to model prototyping, documentation, and testing
• Champion creative uses of existing data to solve business problems with intellectual curiosity
• Produce statistical and data analysis visuals (charts, infographics) to communicate findings clearly and effectively to a non-technical audience
• Collaborate with team members, product managers, and business stakeholders to identify opportunities for new and innovative AI/ML solutions
• Analysis areas could include Onboarding Credit, Ongoing Credit, Marketing segmentation, Voice-based analysis, Text mining, Sentiment analysis, Risk quantification, and Risk-based pricing

Requirements

• 4-7 years of experience in Data Science and the Financial Industry, preferably in Credit or Lending
• Master's degree in mathematics, statistics, computer science, or data science
• Experience in transforming existing processes with AI/ML-based approaches
• Proficiency in data manipulation. Excellent SQL and Python skills for data wrangling and ETL
• Hands-on AWS / cloud experience deploying and operating production ML services (compute, storage, IAM, containerized deployment)
• Experience building or maintaining production applications and services, not just models in notebooks. You should be comfortable owning software in production
• Experience with dashboard tools such as PowerBI or other visualization tools
• Experience building credit or risk models for Financial Services, Lending, or Insurance
• Experience in validating models to identify ongoing improvements
• Rock solid data science skillset: Exploratory Data Analysis, Feature Engineering, Fitting, Tuning, and Comparing models, and managing the model Lifecycle
• Experience with statistical modeling and data analysis using programming languages such as Python
• Experience in ML engineering, cloud-based deployment, and machine learning model lifecycle management
• Knowledge of best practices for financial and lending models (model risk management, model governance, and fair-lending considerations) is a big plus
• Comfort using modern AI and LLM tools to make your own analysis and modeling more efficient (a plus)
• Experience with dbt (major plus)

Benefits

• Competitive salary
• Local & National Health Insurance
• Dental and Vision insurance
• Group Medical Bridge
• 401k with Match
• ID Protection: 100% covered by the company
• Life Insurance: 100% covered by the company
• Generous PTO and holidays
• Growth and development opportunities
• Dynamic and collaborative work environment
• Company events and team-building activities