The Credit Services Risk Management team is a large and complex critical function for company success. We are staffed with highly-skilled and motivated individuals with a large emphasis on analytical abilities & problem solving skills. The Associate Data Scientist will build predictive models used for underwriting and/or collections functions. This person will research and recommend new data sources to improve models and design tests to measure the effectiveness for various strategies implemented.MAJOR DUTIES AND RESPONSIBILITIES
- Responsible for the entire end-to-end data science process from ETL to building models, to deploying the model into the workflows to measuring the financial impact.
- Partner with others to implement models in production and conduct post-launch testing and enhancement
- Actively and consistently support all efforts to simplify and enhance the customer experience
- Responsible for the selection of appropriate algorithms and execution
- Responsible for interpretation of results – for both causal inferences and predictive effectiveness
- Synthesize appropriate recommendations for action and changes
- Present findings, suggested actions and changes to a broad audience, and manage follow-ups and execution
- Help teach and explain techniques and tools used to a broad set of business-intelligence, data, and analytics professionals with varied backgrounds
- Provide coaching and mentoring to achieve a high-performing team
- Manage internal client relationships, including issue resolution, and overall accountability for results and client satisfaction
- Exercise thought leadership and discretion in tailoring the tools, approaches, and data used to meet the needs of the particular problem
- Perform other duties as required
- Predictive analysis experience using SAS/Python/R;
- Experience in building Logistic Regression models, Random Forest models, XGBoost models, and Experimental Design.
- Experience in data pre-processing and exploratory data analysis using a variety of techniques
- Understand the theoretical background of each statistical test and model, inside and out.
- Basic understanding of data architecture, data warehouse and data marts
- Ability to communicate orally and in writing in a clear and straightforward manner
- Ability to plan, prioritize and organize effectively
- Ability to adapt to change
- Detail oriented, self-motivated, proactive and results driven
- Highly energetic; ability to partner across business lines; a go-getter who seeks out information and does not wait for others to reach out
- Strong expertise in SQL.
- Experience in using large databases; conducting complex analysis using more than one languages above
- Expert-level logical and analytic skills
- Broad experience and solid theoretical foundation on the modeling process using a variety of algorithms
- Demonstrated ability and desire to continually expand skill set, and learn from and teach others
- Ability to explain complex analysis results in an easy-to-understand language
- Advance skills in Excel, PowerPoint and Access
- Excellent quantitative analysis skills
- Ability to create conceptual frameworks enabling the analysis of varied business problems
B.S. in quantitative sciences, including statistics, engineering, computer science, Business with focus on analytics. M.S. in Statistics or Data Science will be highly preferredRelated Work Experience
- 2+ years experience solving business problems through deep analytics and with predictive modeling techniques (with a Bachelor’s Degree) OR,
- 1+ years experience solving business problems through deep analytics (with a Masters Degree)
- Industry experience in Financial services, insurance or actuarial services or medical research preferred but not required
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