Lead Data Scientist II

Best Egg•Wilmington, DE

1d•$120,000 - $140,000•Hybrid

About The Position

Data is at the heart of everything we do. Join a Data Science team working at the cutting edge within our industry and constantly advancing our AI/ML practice. Our Data Science team is dedicated to creating advanced analytics and AI/ML solutions that power innovation and creative insights, pioneer new products, and help our business reach the next level. We work on diverse projects across all business units within the company and have a direct engagement model among data scientists, business stakeholders, the product organization, and cross-functional teams. This position is central to driving marketing decisions through the design and development of machine learning solutions. This role will focus on building and improving marketing models that drive critical prospect and existing-customer targeting decisions. In addition, you will collaborate with marketing and analytics partners to integrate models into marketing strategies, improve campaign economics, and ultimately support new loan origination. This role is for a data scientist who is passionate about modeling, analytics, and problem-solving—and who wants to see their work directly drive critical business decisions.

Requirements

A master’s degree in a quantitative field (Statistics, Mathematics, Computer Science, Economics, Data Science, Engineering, etc.); Ph.D. preferred.
3+ years of experience developing predictive models or performing advanced analytics.
Strong understanding of statistical modeling and machine learning fundamentals.
Proficiency in Python (e.g., pandas, numpy, scikit-learn) and SQL.
Ability to clearly communicate analytical findings to both technical and non-technical audiences.
Demonstrated ownership, curiosity, and ability to deliver high-quality results.
Ability to commute to Best Egg’s Wilmington office at least once a week.

Nice To Haves

Experience in marketing campaigns, financial services, or other regulated industries.
Exposure to cloud environments and modern data tooling.
Familiarity with model monitoring, validation, and model governance concepts.
Interest in using AI tools (e.g., ChatGPT, Claude, Gemini) to accelerate modeling and analysis.

Responsibilities

Build high-performance ML models that improve prospect response predictability and customer outcomes.
Build end-to-end machine learning pipelines including data extraction, feature engineering, model development, performance evaluation, and implementation.
Explore rich data assets to uncover trends, identify key risk drivers, and generate insights.
Manage the full modeling lifecycle: model design, data preparation and exploration, feature engineering, model development, evaluation, deployment, monitoring, and documentation.
Design experiments and challenger models to test new ideas and drive innovation.
Contribute to audit-ready documentation and support model validation and governance processes.
Leverage modern AI technology and tools to improve workflow, enhance modeling performance, establish and promote best practices.
Work cross-functionally to ensure models are explainable, transparent, and aligned with business goals and regulatory expectations.
Translate analytical findings into recommendations for strategy, pricing, and other business decisions.
Manage complex operational and conceptual tasks and problems that require innovative thinking, as well as the professional and personal ability to create novel solutions.
Interface regularly with stakeholders to define solutions and user requirements within moderately complex environments.