This role is 100% remote, but requires applicants to be in KS, MO, or TX.
As a leader on the Credit Portfolio and Collection Analytics team, the core responsibilities include loss loan product credit forecasting model development, portfolio monitoring, prepayment analysis, macroeconomic scenarios, stress factors and qualitative management layer recommendations. You will deliver models and insights for credit portfolio loss forecasting and collection strategies, that drive decision-making, execution and operation in various aspects of business. Success requires analytical savviness, problem-solving sophistication, a willingness to roll up your sleeves and a dedication to make the highest impact possible. A successful candidate has the management skills to lead and scale a team of analysts and developers, is hands-on enough to help them implement your vision, and strategic enough to work with the stakeholders around the company to set that vision. This position will report to the Chief Risk/Credit Officer. Ensures operational compliance and all delivery is effectively and efficiently managed.
ESSENTIAL DUTIES AND RESPONSIBILITIES
• Responsible for attracting, recruiting and growing risk analytics and engineering talent within the team • Create and steer the credit portfolio and collection analytics roadmap. Assist with making technology decisions. • Provide statistical/machine learning guidance for robust risk analysis, experimentation and opportunity identification • Directly managing a team of model analysts/developer and collaborating with a cross-functional team of product managers, engineers, and data scientists • Develop, manage and maintain financial/loss models used to build the various subcomponents of loss forecast • Design, Develop and Deploy advanced machine learning and Artificial Intelligence algorithms/predictive models for use in Credit Portfolio Management, Loss Forecasting, Collections and Operations.
• Evaluate loss forecast model methodologies, monitor portfolio performance metrics and synthesize analysis for presentation to management • Assess, clean, merge, and analyze large datasets adhering to standardized data manipulation techniques and methodology by leveraging R, SAS, Python and/or Apache Spark. • Perform parallel processing computations both within R as well as cluster computing technologies such as Apache Spark. • Prepare risk management presentations for senior management that include analytics on expected portfolio performance and areas of potential risk and/or opportunity
• Ensure model backtesting and ongoing monitoring are performed and reviewed and implement any changes that arise from the results • Perform in-depth analysis, including trends, variances, macro-variables impact, etc for customer behavioral insights and risk mitigation recommendations • Perform scenario analysis, estimating the effects of changes in forecasts and assumptions on expected credit losses on an ongoing basis • Maintain clear, detailed model documentation on our Wiki Server by leveraging reproducible research technologies such as Rmarkdown, IPython, Jupyter Notebook, etc. • Functional lead and point of contact with business partners to support the needs and goals of all portfolios. • Lead analytical projects by leveraging and coaching Data Scientists in the team
• Has the ability to operate with a limited level of direct supervision.
Experience and Education:
• Minimum Master’s degree in highly quantitative field (Statistics, Economics, Mathematics, Engineering, or other quantitatively-oriented degree) required. • At least SIX years of experience in consumer loan loss forecasting from a financial institution in the functioning teams of either risk modeling, credit risk, credit capital or corporate finance. Professional experience waived with at least two years of Data Science or Modeling experience and Ph.D. Degree in highly quantitative field (Statistics, Economics, Mathematics, or other quantitatively-oriented degree), including 3+ years managing a team of individual contributors • Demonstrated proficiency with advanced statistical modeling and substantial experience with machine learning techniques (e.g., Random Forest, Gradient Boosting, LASSO, Elastic Net, Time serious analytics etc).
Knowledge of penalized regression and classification methods a plus. • Strong data skills, with ability to conduct substantial data munging/engineering. • Proficiency with SAS and R, Python, or Java; expertise with versioning software (e.g., Git), big data solutions and data processing frameworks (e.g., Spark, Hadoop).
• Experience with at least four database technologies such as MSSQL Server, SAS Datasets, Hadoop, Apache Hive/Impala, Spark, Redshift, HBASE, Kafka, Spark Streaming, Neo4j, Teradata, Oracle, MySQL, DB2, Amazon AWS, Cassandra, PostgreSQL, NoSQL, JSON & XML parsing, etc. • Proven experience working in fast-paced environment with ever-changing demands. • Superior communication skills for communication with Risk Management peers and executive team. • Proficiency of contemporary supervised and unsupervised data mining techniques a plus.
Required Skills and Abilities:
• Motivation Skills - History of achieving aggressive organizational goals and objectives, conveying sense of urgency while moving beyond challenges and obstacles. • Comfortable formulating actionable insights and recommendations from analytics into presentations (using PowerPoint, Tableau, etc.) and presenting results to various levels of management
SUPERVISORY RESPONSIBILITIES Manages the planning, organization, and controls for a major functional area. • Leads and supports staff in areas of staffing, selection, training, development, coaching, mentoring, measuring, appraising and rewarding performance and retention. Leads by example and models behaviors that are consistent with the company’s values • Thinking and Administrative Skills - Solid analytical and problem solving skills. Ability to analyze trends and suggest solutions to challenges. • Achieve Successful Results – Takes the initiative to get things done. • Demonstrates Adaptability – Works effectively in the face of stress, ambiguity, difficult situations and shifting priorities. • Innovates – Challenges the status quo thinking to generate new ideas; takes open minded approach to situations. • Communication Skills - Refined written and verbal communication skills. Ability to foster open communications, listen effectively and build strong partnership networks. • Technological Competence – Extensive knowledge of R, Python, Scala, Java, SAS, MATLAB, SQL, and/or SPSS and risk management technology with the ability to leverage such tools to improve the organization’s decision making criteria. • Direct experience developing and implementing loss forecasting models preferred