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Credit Risk Data Science Jobs in Ohio (NOW HIRING)

Ability to access and query a multitude of databases and create and maintain data sets as ... Continually recognized with CRO Leadership Awards from Life Science Leader magazine based on ...

Ability to access and query a multitude of databases and create and maintain data sets as ... Continually recognized with CRO Leadership Awards from Life Science Leader magazine based on ...

Partner closely with Data Science to guide the development and implementation of predictive models and risk frameworks. * Collaborate with Product and Engineering teams to translate credit strategy ...

... data analysis, and other reasoning exercises related to finance management A current, in progress ... Credit Risk jobs in Wyoming, United States . We're unlocking community knowledge in a new way.

Spark/Python, Data Science and Analytics, Optimization Frameworks, Graph/Linkage Analysis, Data ... Collaborates with the line of business, Finance, and Risk partners to assess and establish credit ...

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Credit Risk Data Science information

What are the key skills and qualifications needed to thrive as a Credit Risk Data Scientist, and why are they important?

To thrive as a Credit Risk Data Scientist, you need strong analytical skills, proficiency in statistical modeling, and a solid background in finance, mathematics, or a related field, often supported by an advanced degree. Familiarity with programming languages like Python or R, experience with machine learning frameworks, and knowledge of credit risk modeling tools such as SAS or SQL are typically required. Critical thinking, attention to detail, and effective communication are vital soft skills for interpreting data and collaborating with stakeholders. These abilities are crucial for building accurate risk models, informing strategic decisions, and ensuring regulatory compliance in financial institutions.

How does a Credit Risk Data Scientist typically collaborate with other teams within a financial institution?

Credit Risk Data Scientists often work closely with credit analysts, risk managers, and IT professionals to develop, validate, and implement models that assess borrower risk. They frequently participate in cross-functional meetings to translate complex analytical findings into actionable business insights. Collaboration with compliance and regulatory teams is also common to ensure that risk models meet current regulatory standards. Effective communication and teamwork are essential, as the role bridges technical model development and practical risk management decisions.

What is Credit Risk Data Science?

Credit Risk Data Science is a specialized field that uses statistical analysis, machine learning, and data modeling techniques to assess and predict the likelihood that a borrower will default on a loan or credit obligation. Professionals in this field analyze large datasets from financial transactions, credit reports, and market trends to develop models that help financial institutions make informed lending decisions. Their work helps manage risk, set appropriate interest rates, and comply with regulatory standards. By leveraging advanced analytics, credit risk data scientists play a crucial role in minimizing losses and maximizing profitability for banks and lenders.
What job categories do people searching Credit Risk Data Science jobs in Ohio look for? The top searched job categories for Credit Risk Data Science jobs in Ohio are:
What cities in Ohio are hiring for Credit Risk Data Science jobs? Cities in Ohio with the most Credit Risk Data Science job openings:
Vice President, Data Scientist - Credit Risk, Risk Insights - Chase 360

Vice President, Data Scientist - Credit Risk, Risk Insights - Chase 360

JPMorgan Chase & Co

Columbus, OH

Full-time

Medical, Retirement

Posted 6 days ago


JPMorgan Chase & Co. rating

8.1

Company rating: 8.1 out of 10

Based on 466 frontline employees who took The Breakroom Quiz

46th of 141 rated banks


Job description

Join a high-impact team shaping credit strategy across consumer and small business lending at JPMorganChase. Leverage Chase's crosslineofbusiness data and your advanced analytics skills to surface emerging risks, guide portfolio decisions, and protect customers through cycles. You'll operate at the intersection of data science, macro insights, and credit risk, presenting timely intelligence to senior CCB (Consumer and Community Bank) Risk leaders. If you thrive in dynamic environments and love turning complex data into clear actions, this role is for you.

As a Vice President, Data Scientist in the Chase 360 Payment Analytics team within CCB Risk Insights, you will leverage crossLOB customer data to generate insights on consumer and smallbusiness health, inform and influence credit strategy, and build attributes that power credit models and decisions. You will own endtoend analytical work-from data engineering and feature development to modeling, interpretation, and executive storytelling-delivering timely, highimpact insights and dashboards that influence strategic choices across Card, Auto, Home Lending, and Business Banking. You will independently research emerging risks, synthesize external publications and data releases, and partner across Chase 360 to drive scalable solutions and measurable business outcomes.

Job Responsibilities:

  • Generate timely insights on consumer and smallbusiness health using crossLOB data to identify, quantify, and monitor emerging credit risks.
  • Inform and influence credit strategies across Card, Auto, Home Lending, and Business Banking with datadriven recommendations and scenario analysis.
  • Engineer and maintain highquality attributes/features to support credit models, segmentation, and policy execution.
  • Design and execute advanced analytics (e.g., risk segmentation, earlywarning signals, stress indicators) to track portfolio trends and headwinds.
  • Build and automate dashboards and recurring reports that translate complex analytics into clear, actionable leadership narratives.
  • Conduct independent research on macro, industry, and payment trends; connect external developments to portfolio risks and opportunities.
  • Analyze peer publications and public data releases to produce differentiated viewpoints for CCB Risk leadership.
  • Partner with data engineering, model, and product teams to operationalize insights and ensure scalability, resiliency, and governance.
  • Manage crossfunctional projects endtoend, aligning stakeholders, defining milestones, and delivering on time in a fastpaced environment.
  • Communicate findings to technical and nontechnical audiences, using crisp narratives, visuals, and executiveready materials.
  • Champion best practices in code quality, reproducibility, and model/metric documentation to elevate team capabilities.

Required Qualifications, Capabilities, and Skills:

  • Advanced degree (MS preferred) in statistics, econometrics, or related quantitative field with minimum 7 years in risk management or quantitative roles; or BS with minimum 8 years relevant experience.
  • Experience in consumer financial services with a focus on credit risk analytics and portfolio monitoring across the credit lifecycle.
  • Strong Python proficiency (data wrangling, modeling, visualization, automation) and productiongrade code practices.
  • Advanced SQL skills with proven ability to query, transform, and QC large, complex datasets from multiple sources.
  • Demonstrated ability to build, maintain, and validate attributes/features for credit models and strategy execution.
  • Track record of delivering timecritical analytical reports/dashboards to senior stakeholders with clear, actionable insights.
  • Strong quantitative problemsolving, hypothesisdriven analysis, and experimental design skills.
  • Excellent communication skills, translating technical analyses into concise recommendations for leadership.
  • Selfstarter with ownership mindset; proven ability to drive ambiguous problems to scalable solutions under tight timelines.
  • Familiarity with integrating external data/publications and macro trends into credit risk assessments.
  • Project management experience leading crossfunctional initiatives from scoping through delivery and adoption.

Preferred Qualifications, Capabilities, and Skills:

  • Experience with payments data, spend behaviors, and earlywarning indicators tied to consumer and smallbusiness health.
  • Knowledge of credit risk modeling techniques and performance monitoring.
  • Proficiency with data visualization/BI tools (e.g., Tableau, Power BI) for automated reporting.
  • Familiarity with cloud data platforms and distributed computing (e.g., AWS, Spark) for largescale analytics.
  • Experience partnering across business lines and risk functions to align strategies and implement analytics at scale.
  • Strong sense of learning agility-comfort quickly adopting new tools, methods, and business concepts.

Chase is a leading financial services firm, helping nearly half of America's households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs. 

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions.  We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. 

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

Equal Opportunity Employer/Disability/Veterans

Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We're proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions - all while ranking first in customer satisfaction.

The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.

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