Job purpose
The Data Scientist is responsible for performance analysis, through data science, machine learning, and advanced statistical analytics techniques in the areas of fraud, collections, operations, and companywide cross-functional projects. This position will utilize advance statistical skills to analyze data, fraud losses, portfolio performance trends, and forecasting skills to support credit risk functions. The successful Data Scientist will be self-motivated, highly analytical, and detail-oriented.
Duties and responsibilities
Applies innovative and scientific/quantitative analytical approaches to draw conclusions and make recommendations to answer business objectives and drive change.
Develop analytics regarding fraud, fraud losses, and identifying key drivers with focus on direct mail and digital underwriting.
Utilizes advanced statistical analytics to assess fraud risk, opportunities, and effectiveness and translates results into meaningful solutions to enhance decision-making.
Conducts ad hoc research projects incorporating project design, data collection and analysis, summarization of findings, and presentation of results.
Applies advanced knowledge to produce advanced analytical material for discussions with cross-functional teams to understand complex business objectives and influence solution strategies.
Interacts with stakeholders to understand their business questions, crafting the methodology, to mine/analyze datasets and delivers a final insightful recommendations to stakeholders.
Minimum Qualifications
Bachelor's degree in Finance, Statistics, Mathematics, Actuarial Sciences, or other quantitative disciplines. Preferred 2+ years of related experience in a quantitative role
2+ years of related experience in quantitative role or s
Experience in data mining, modeling, and analyzing analytic findings using SQL, SAS or R
Moderate to Expert level skills in Microsoft Office Suite (Excel, Access, and Outlook a must)
Must pass a drug screen, criminal, and credit background checks.
Preferred Qualifications
3+ years of 1st or 2nd LOD quantitative experience inside a highly complex, large financial institution
Credit risk modeling experience with strong ability in analytical problem-solving. Advanced SAS experience; Python and machine learning modeling a plus
Critical Competencies
Excellent oral and written communication skills.
Excellent organizational skills with the ability to prioritize and handle multiple tasks and responsibilities simultaneously.
Utilize appropriate analysis, judgment and logic when solving problems and making decisions.
Demonstrated ability to apply complex financial and statistical principles.
Effective written and verbal presentation skills; able to communicate well with Senior and Executive Management.
Innovative problem solving, quantitative and analytical abilities.
Detail-oriented.
Able to work with minimal supervision.
Flexible, proactive working style.
Adaptive to a team environment.
Working conditions
This position works in an office environment.