Job Description – Data Scientist
Department: Risk and Analytics
Reports To: Director of Risk Modeling
Position location: This is a limited remote position. Candidates MUST reside in KS, MO, OK or TX. No exceptions.
At Caliber Financial Services, we rely on insightful data to power our systems and solutions. We’re seeking a Data Scientist to deliver that insight to us on a daily basis. Our ideal team member would not only need to have statistical methodology expertise and programing skills such as SQL, Python, R, and SAS,, but a natural curiosity and creative mind that’s easy to find. As you mine, interpret, and clean our data, we will rely on you to ask questions, connect the dots, and uncover opportunities that lie hidden within—all with the ultimate goal of realizing the data’s full potential. You will join a team of data specialists but will “slice and dice” data using your own methods, creating new visions for the future.
Primary Responsibilities:
- Design, Develop and Deploy advanced machine learning and Artificial Intelligence algorithms/predictive models for use in Underwriting, Customer Management, Marketing, Portfolio Management and Operations.
- Assess, clean, merge, and analyze large datasets adhering to standardized data manipulation techniques and methodology by leveraging SQL, R, SAS, Python and/or Databricks Spark.
- Perform parallel processing computations within Python/R/SAS environment as well as cluster computing technologies such as Databricks Spark.
- Design, Develop and Deploy multiple linear and nonlinear models for testing, development and deployment into our underwriting engine in the application of risk management in all of Caliber’s acquisition channels.
- Efficiently apply data mining methodologies to minimize credit/fraud losses, maximize response and approval rates, and develop methods to enhance profitability of Caliber products.
- Provide insights and guidance of third-party data from data mining results, such as Factor Trust/Transunion, Clarity/Experian, and Equifax to include knowledge of products and data available, products to purchase or discontinue, cost benefit analysis of retrospective analysis, effective use of variables, data dictionaries as well as advantages and limitations.
- Maintain clear, detailed model documentation.
Education & Required Skills and Abilities:
- Minimum Master’s degree in highly quantitative field (Statistics, Economics, Mathematics, Engineering, or other quantitatively-oriented degree) required.
- Minimum 1-2 years previous experience working in financial risk analytics required.
- Demonstrated proficiency with advanced statistical modeling and substantial experience with machine learning techniques (e.g., Random Forest, Gradient Boosting, LASSO, Elastic Net, etc). Knowledge of penalized regression and classification methods a plus.
- Strong SQL data operation & programming skills, with ability to conduct substantial data munging and data engineering.
- Proficiency with Python, R, or SAS; expertise with versioning software (e.g., Power BI or Tableau), big data solutions and data processing frameworks (e.g., Spark, Hadoop).
- Can do attitude and can work in fast-paced environment with ever-changing demands.
- Superior communication skills for communication with Risk Management peers and executive team.
- Experience with database technologies such as Oracle, PostgreSQL, SQL Server, or Databricks a plus.
- Proficiency of contemporary supervised and unsupervised data mining techniques a plus.
Work Environment
This is a limited remote position. Candidates MUST reside in KS, MO, OK, or TX in order to be considered. No exceptions.