Data Science Analyst 2

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Job Summary
Under supervision and guidance, the Data Science Analyst, 2 applies data science in advanced analytics such as predictive modeling and data mining in a big data environment in order to deliver predictive models and insights. The Data Science Analyst, 2 produces insights that encompass the different product types and channels and maintain regulatory standards. The Data Science Analyst, 2 assists with ensuring accurate and timely implementation of solutions, quantifying the overall financial impact to the business, and communicating results.

Essential Job Functions
Analytics – under supervision and guidance, completes the following: 1) extracts and samples data, conducts data integrity checks and applicable data pre-processing such as treatment of missing values and outliers, 2) conducts exploratory data analysis for preliminary data insights to drive the selection of modeling approach that best addresses the business problem, 3) reveals hidden data patterns by data mining using unsupervised learning techniques such as clustering analysis and factor analysis, 4) conducts feature engineering to create/derive model predictors with strong predictive power, 5) trains/tunes classification/regression models by applying supervised learning techniques such as generalized linear models assuming applicable underlying distributions such as logit and gamma, tree-based models such as decision trees, random forest, boosted trees, etc., and neural net models, and 6) conducts proper model test/validation, diagnoses and fixes model issues (e.g., over-fitting) when applicable. Sizes the impact of using the models in production as part of the current strategy. Presents results and business case to manager. Provides support for implementation and monitoring of solutions that are implemented.
Collaboration – under supervision and guidance, translates analytical results into useful recommendations for review with manager. Demonstrates strong verbal and written communication skills when working with internal partners and when presenting results to various audiences. Develops foundational knowledge of credit card operations, banking, financial, loyalty rewards, retail, and credit card regulations while working with the business. Collaborates with other data scientists in the company to share best practices and data science innovations.

Data Science innovation – with direction from leader, researches industry trends in data science of new tools, emerging algorithms, advanced platforms, and alternative data to enhance modeling effectiveness and efficiency. Conducts use case testing for new tools/techniques/platforms/data and provides user input/feedback.
Model risk management - develops foundational knowledge on common model risks and related regulatory requirements; applies proper 1st line of defense controls during model development process to minimize model risk; creates comprehensive model governance documentation and archives model data, scripts, and results; collaborates with model risk management partners to complete model validation/auditing; completes remediation as required by model governance process.
Reports to: Manager or higher
Working Conditions/ Physical Requirements: Normal office environment
Direct Reports: None
Minimum Qualifications
Degree Required: Bachelor’s Degree
Area of Study: Statistics, Mathematics, Engineering, Data Science, Economics, Computer Science, or another quantitative field
Years of Work Experience Required: 2 to 5 years
Type / focus of work experience required: Related work experience
Preferred Experience

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Degree Preferred: Master’s Degree, PhD
Area of Study: Statistics, Mathematics, Engineering, Data Science, Economics, Computer Science or another quantitative field
Years of Work Experience Preferred: 3+ years
Type / focus of work experience preferred: Professional hands-on experience in developing statistical models/machine learning models and conducting data mining to solve business problems. Experience in extracting and processing large files/data sets. Experience interpreting model results and translating insights into business recommendations.
About Bread Financial
At Bread Financial, you’ll have the opportunity to grow your career, give back to your community, and be a part of our award-winning culture. We’ve been consistently recognized as a best place to work in many markets and we’re proud to promote an environment where you feel appreciated, accepted, valued, and fulfilled—both personally and professionally. Bread Financial supports the overall wellness of our associates with a diverse suite of benefits and offers boundless opportunities for career development and non-traditional career progression.
Bread Financial is a tech-forward financial services company providing simple, personalized payment, lending and saving solutions. The company creates opportunities for its customers and partners through digitally enabled choices that offer ease, empowerment, financial flexibility and exceptional customer experiences. Driven by a digital-first approach, data insights and white-label technology, Bread Financial delivers growth for its partners through a comprehensive product suite, including private label and co-brand credit cards, installment lending, and buy now, pay later (BNPL). Bread Financial also offers direct-to-consumer solutions that give customers more access, choice and freedom through its branded Bread Cashback American Expressregistered Credit Card and Bread Savings products.
Headquartered in Columbus, Ohio, Bread Financial is powered by its 7,500+ global associates and is committed to sustainable business practices.

• All job offers are contingent upon successful completion of credit and background checks.
• Bread Financial is an Equal Opportunity Employer.
  

Job Family
Data and Analytics
Job Type
Regular