We are seeking a motivated and analytical Mid-Level Data Scientist / Quantitative Analyst to join our growing team. This role is ideal for an individual with experience working with large datasets, developing analytical models, and building quantitative solutions within data-driven platforms and systems. Our company develops decision engines, underwriting systems, model execution platforms, data platforms, and business intelligence solutions focused on the consumer and commercial lending industries. The ideal candidate is excited about solving complex quantitative and analytical problems in a highly data-centric and model-driven environment while collaborating closely with software engineering, analytics, and business teams. Responsibilities Develop, evaluate, and maintain statistical, predictive, and analytical models used within underwriting and decisioning systems Analyze large datasets to identify trends, risk characteristics, and business insights Support the development and enhancement of credit risk, underwriting, and financial decision models Build data pipelines, analytical workflows, and reusable data processing solutions Collaborate with software engineers to integrate models and analytical solutions into production systems Write and optimize SQL queries for data extraction, transformation, and analysis Work with cloud-based data infrastructure and analytical environments, primarily within Amazon Web Services (AWS) Develop dashboards, reporting datasets, and analytical outputs to support business and operational decision-making Perform exploratory data analysis, feature engineering, and model validation activities Participate in code reviews, documentation, and analytical best practices Communicate technical findings and model behavior to both technical and non-technical stakeholders Required Qualifications 3+ years of professional experience in data science, quantitative analytics, statistical modeling, or related fields Strong proficiency in Python and experience using analytical libraries such as Pandas, NumPy, SciPy, or Scikit-learn Strong understanding of statistical modeling, predictive analytics, and quantitative problem-solving Working knowledge of SQL and relational databases Experience working with large datasets and data-intensive applications Experience using Git-based version control workflows Familiarity with cloud computing environments, preferably AWS Strong analytical, problem-solving, testing, and debugging skills Ability to communicate technical concepts and analytical findings clearly to a variety of audiences Preferred Qualifications Experience working within financial services, lending, underwriting, risk, or credit-related platforms Familiarity with machine learning workflows, model evaluation techniques, and feature engineering Experience developing or supporting productionized analytical or machine learning systems Exposure to ETL pipelines, data warehouse technologies, and distributed data processing Experience with BI and data visualization platforms Familiarity with REST APIs and integrating analytical systems into software platforms Experience with frontend technologies or dashboarding frameworks is a plus Familiarity with Agile software development methodologies Understanding of underwriting strategies, credit policy, or financial decision logic Nice to Have Experience supporting real-time decisioning or scoring systems Exposure to workflow orchestration or event-driven architectures Experience with model monitoring, observability, and performance tracking Understanding of security and compliance considerations in financial systems

Benefits:

401(k) 401(k) matching Dental insurance Employee assistance program Flexible spending account Health insurance Health savings account Life insurance Paid time off Referral program Retirement plan Vision insurance

Experience:

Software deployment: 3 years (Preferred) Ability to

Commute:

Dublin, OH 43017 (Preferred)

Work Location:

Hybrid remote in Dublin, OH 43017