BHG Financial is looking to leverage advanced analytics and data science to drive strategic decision-making, improve operational efficiency, and support organizational growth by developing and deploying predictive models for risk assessment, credit scoring, pricing, and loan origination.
Requirements
- Proficiency in statistical modeling and data analysis using R or Python, with solid experience working with large datasets and writing complex SQL queries.
- Experience working in Databricks or similar cloud-based analytics environments.
- Proficiency with data visualization tools such as Power BI, Tableau, or R Shiny.
- Experience leveraging generative AI tools (e.g., ChatGPT, Claude, DALL·E) to enhance productivity, automate content creation, and support data-driven decision-making.
Responsibilities
- Design, build, and maintain predictive models using advanced statistical and machine learning techniques to support risk assessment, credit scoring, pricing strategies, and loan origination optimization.
- Continuously monitor and enhance model performance to adapt to changing business needs.
- Evaluate internal and external data sources to identify valuable features, improve model accuracy, and uncover new opportunities for innovation.
- Apply the most effective analytical methods to solve complex business problems, generate actionable insights, and recommend data-driven strategies that improve decision-making and operational efficiency.
- Establish robust monitoring frameworks to detect emerging risks and opportunities, ensuring timely and proactive responses.
- Partner with cross-functional teams to identify high-impact use cases, translate analytical findings into compelling narratives, and deliver clear, actionable recommendations to both technical and non-technical audiences.
Other
- 3+ years of hands-on experience in data science, with a strong preference for candidates with a background in the FinTech or Financial Services industry.
- Strong analytical and problem-solving skills, with a proven ability to synthesize quantitative and qualitative data to answer complex business questions.
- Excellent communication skills, including the ability to present technical findings clearly and persuasively to both technical and non-technical audiences.
- A self-starter mindset with strong organizational skills, capable of managing multiple priorities in a fast-paced, dynamic environment.
- Bachelor’s degree in quantitative discipline such as Statistics, Mathematics, Data Science, Operations Research, Engineering, or a related field; an advanced degree (master’s or Ph.D.) is strongly preferred.
