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Credit Risk Data Science Jobs in Ohio (NOW HIRING)

Reviews credit information and makes decisions related to credit limits and credit holds for ... Ability to access and query a multitude of databases and create and maintain data sets as ...

Reviews credit information and makes decisions related to credit limits and credit holds for ... Ability to access and query a multitude of databases and create and maintain data sets as ...

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Credit Risk Data Science information

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 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.
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:
Quant Analytics Manager - Credit Risk Modeling

Quant Analytics Manager - Credit Risk Modeling

Keybank

Brooklyn, OH

Full-time

Posted 15 days ago


KeyBank rating

8.3

Company rating: 8.3 out of 10

Based on 95 frontline employees who took The Breakroom Quiz

30th of 146 rated banks


Job description

Location:

4900 Tiedeman Road, Brooklyn Ohio

ABOUT THE JOB (JOB BRIEF)

The Quantitative Analytics Manager is primarily responsible for leading the development and validation of predictive and machine-learning models for specific business needs using statistics, advanced mathematical techniques, and/or computer science. The Quantitative Analytics Manager leverages advanced mathematical knowledge, analysis, partnerships, and business knowledge to provide solutions to predictive and prescriptive questions such as "What will happen next?" and "What will we do?". Projects undertaken by the Quantitative Analytics Manager are often broad in scope across multiple business segments and involve guiding a team and/or project through providing solutions to business problems leveraging statistics, best practices or emerging techniques, and quantitative tools / techniques. Success factors include: Demonstrating leadership through strong communication skills, addressing conflict, coaching others on developing technical skills; managing competing priorities and presenting holistic, thoughtful analyses to answer partners' problem statements; prioritizing multiple projects and managing to tight deadlines; establishing reputation as an effective and collaborative partner; Communicating technical theories, observations, and models to a non-technical audience; Leveraging knowledge of strategy, business, and competition to connect day-to-day work of team to the "bigger picture" and driving efficiency in solution delivery

ESSENTIAL JOB FUNCTIONS

  • Create and leverage models, inferential statistics and prescriptive analysis to proactively solve business problems answering the questions "What will happen and what should we do about it?"
  • Often responsible for large, complex problems that have broad implications and are less frequent
  • Recommend solutions based on understanding of the context, connections, and conclusions
  • Reviews deliverables; proactively coaches others on approach and work product
  • Lead and evangelize on best practices of capturing and retaining data
  • Coordinate with data stewards and anticipate needs process/procedures
  • Make continuous improvements to data procedures, including data efficiency
  • Recommend best analysis method for the situation

REQUIRED QUALIFICATIONS

  • Master's degree (or equivalent) in statistics, mathematics, economics, financial engineering, data sciences, predictive modeling, or other quantitative disciplines and at least 5 years of relevant experience; or Bachelor's degree (or its equivalent) in statistics, mathematics, economics, financial engineering, data sciences, predictive modeling, or other quantitative disciplines and at least 6 years of relevant experience

PREFERRED QUALIFICATIONS:

  • 10 or more years developing scorecard models in the financial services industry in credit risk management or fraud.

DATA LITERACY

  • Understanding of:
    • Best practices for capturing / retaining data
    • Pros / Cons of competing analysis methods
  • Experience leading by:
    • Partnering with others to anticipate and understand needs process/procedures
    • Leading information practices / policies / procedures
    • Setting standards and expectations for data analysis tools and techniques; ensuring compliance with application
    • Promoting increased efficiency of data analysis by advocating clearer data requirements

TECHNOLOGY & TECHNIQUES

  • Advanced Microsoft Office Suite
  • SQL/NoSQL
    • Relationship data structure
    • Selecting and retrieving data including unstructured data retrieval, archival, and ETL
    • Databases
  • Advanced Python/R/SAS:
    • Databases
    • Efficient coding
    • Can build strong code controls and translate code into high-level commentary
  • Understanding of and ability to leverage:
    • Cloud-based computing
    • Distributed computing

MODEL BUILDING & MAINTENANCE

  • Ability to:
    • Establish standards and best practices; forecast future modeling tools / techniques
    • Identify, employ, and evangelize emerging techniques from industry / research
    • Coach others on data modeling methods / techniques
    • Facilitate sessions for complex data models
    • Assess and understand risks; contingency plans
    • Communicate observations to senior executives
    • Translate technical observations to a non-technical audience

EXPECTED COMPETENCIES

  • Leadership: Demonstrated leadership; may have direct reports; Assumes accountability for their work; Sought out for advice; Proactively coaches and guides the work of others; Manages the integration of activities typically within own team; Demonstrates executive presence; Offers an opinion, contributes to the conversation
  • Partnering / Influencing: Demonstrated ability to engage and partner at mid to senior leadership levels; Established reputation and track record as an effective and collaborative partner; Coaches and develops relationship building skills in others; Demonstrates managerial courage; willing to dissent from others; leverages organizational and professional savvy and persuasive skills to influence others
  • Business Acumen: Understands LOB and KeyCorp strategy; Leverages knowledge of our competition and the business to anticipate needs and make recommendations; Understands how business works; Contributes materially to LOB strategy
  • Critical Thinking / Problem Solving: Critical thinker: able to anticipate business partner needs; Sees the "bigger picture"; Advises leaders to make informed decisions based on keen critical thinking and problem-solving ability; Sought out for perspective and guidance with tackling challenges; Can make decisions; considers longer term business strategy in recommending solutions
  • Communication: Excellent writing skills; develops writing skills in others; Recognizes the need to deliver the right message at the right time through the right channel; Articulates the broad implications / impact of the message; Anticipates and addresses conflict; Addresses challenging situations; does not shy away from a tough conversation; Strong presentation development; can coach and guide others to get to the appropriate level of detail and send an effective message; Comfortable presenting to senior levels, easily adapts / changes course, presents with confidence; Demonstrates executive presence

COMPENSATION AND BENEFITS

This position is eligible to earn a base salary in the range of $116,000.00 - $216,000.00 annually. Placement within the pay range may differ based upon various factors, including but not limited to skills, experience and geographic location. Compensation for this role also includes eligibility for incentive compensation which may include production, commission, and/or discretionary incentives.

Please click here for a list of benefits for which this position is eligible.

Key has implemented an approach to employee workspaces which prioritizes in-office presence, while providing flexible options in circumstances where roles can be performed effectively in a mobile environment.

Job Posting Expiration Date: 07/20/2026 KeyCorp is an Equal Opportunity Employer committed to sustaining an inclusive culture. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, genetic information, pregnancy, disability, veteran status or any other characteristic protected by law.

Qualified individuals with disabilities or disabled veterans who are unable or limited in their ability to apply on this site may request reasonable accommodations by emailing HR_Compliance@keybank.com.

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About KeyBank

Sourced by ZipRecruiter

Key is one of the nation's largest bank-based financial services companies. Key provides deposit, lending, cash management, insurance, and investment services to individuals and businesses in 15 states under the name KeyBank National Association through a network of more than 1,200 branches and more than 1,500 ATMs. Key also provides a broad range of sophisticated corporate and investment banking products, such as merger and acquisition advice, public and private debt and equity, syndications, and derivatives to middle market companies in selected industries throughout the United States under the KeyBanc Capital Markets trade name.

Industry

Banking and credit intermediation

Company size

10,000+ Employees

Headquarters location

Cleveland, OH, US

Year founded

1849