Data Scientist

About the Role

Key Responsibilities

• Design and develop novel machine learning models tailored to financial applications such as risk assessment, borrower behavior prediction, churn modeling, and pricing strategy.
• Prototype and productionize LLM-powered tools and workflows for knowledge extraction, report generation, automated customer service, and internal efficiency gains.
• Partner with engineers to ingest, process, and refine structured and unstructured data from internal systems, cloud environments (AWS), APIs, and external vendors.
• Execute advanced statistical and quantitative analyses to uncover trends, test hypotheses, and provide strategic guidance.
• Identify and evaluate new data sources to enhance model performance and business insight.
• Translate complex technical findings into business-friendly presentations and visualizations (e.g., using Power BI or custom dashboards).
• Drive process automation by integrating programmatic solutions into workflows, minimizing manual touchpoints.
• Stay up-to-date on emerging AI/ML and LLM technologies, assessing their potential applicability to business needs.
• Mentor associate scientists and contribute to a culture of experimentation, collaboration, and data literacy.

Requirements

• 4+ years of experience in data science or applied analytics, preferably in financial services or a related regulated environment, or completion of a bachelor’s/master’s program related to Data Science.
• 2+ years of direct experience designing, developing, and deploying predictive models using Python and ML frameworks.
• Experience working with LLMs and NLP tools (e.g., OpenAI, Hugging Face, LangChain) strongly preferred.
• Hands-on experience with SQL, AWS, and Python libraries such as Pandas, scikit-learn, Keras, or TensorFlow.
• Proven success using ML models to drive impact in business settings (e.g., credit scoring, fraud detection, customer retention).
• U.S. citizenship and the ability to obtain a 6C Federal security clearance are required.

Nice to Have

• Deep understanding of statistical modeling, time-series forecasting, and financial KPIs.
• Familiarity with RAG (Retrieval-Augmented Generation) and fine-tuning LLMs.
• Expertise in MLOps, including model validation, monitoring, and deployment best practices.
• Experience with version control (Git), containerized development (Docker), and collaborative development workflows.
• Strong communication skills, including the ability to present to executive leadership and non-technical stakeholders.
• A self-starter who thrives in dynamic environments and is driven to solve novel problems through data.

Qualifications

• Bachelor's degree in Data Science, Computer Science, Applied Mathematics, Statistics, Economics, or a related quantitative field.

Benefits & Perks

• Medical, dental, vision insurance
• HSA and FSA options
• Generous earned time off
• 401K and student loan repayment programs
• Life insurance & AD&D insurance
• Employee assistance program
• Employee stock purchase program
• Tuition reimbursement
• Performance-based incentive pay
• Short- and long-term disability
• Robust wellness program