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Credit Risk Data Science Jobs in New York (NOW HIRING)

FanDuel

Risk Data Science, Director

Jersey City, NJ

Drive risk data science strategy and execution * Develop and drive risk data science strategy across Sportsbook aligned to business and product goals (revenue, margin, customer outcomes, responsible ...

American Express

Manager - Data Science

Manhattan, NY · On-site

$103K - $174K/yr

Credit & Fraud Risk Finance team delivers fact-based, decision-driven and high-impact Net Loss ... Partner with Data Science and Technology teams to develop and scale innovative solutions, ensuring ...

Optimize Partners

Director, Data Science

New York, NY · Hybrid

Overall 10+ years of experience with data science, credit risk management experience is a definite plus * 2-4 years of credit risk modeling experience * 2+ years of experience with Python programming

IDBNY

Credit Risk Analytics & Modeling

Manhattan, NY · On-site

Risk Management / Credit Risk Management Location: New York, NY (Hybrid - 3 days in office ... Bachelor's degree in Finance, Economics, Statistics, Mathematics, Data Science, or another ...

Reach Financial

Credit Risk Analyst

New York, NY

Credit Risk Analyst/Associate Location: NYC (3-4 days in office; EST hours) Compensation: $90,000 ... Reach Financial's Risk and Decision Science team consists of a group of Data Scientists and ...

Nova Credit

Senior Data Scientist

New York, NY · Hybrid

$168K - $199K/yr

... of Data Science. RESPONSIBILITIES: * Research and develop credit risk predictive models based on cross-border consumer performance data or bank transaction data. * Research and develop bank ...

Reach Financial

Credit Risk Analyst

New York, NY · On-site

Credit RiskAnalyst/Associate Location: NYC (3-4 days in office; EST hours) Compensation: $90,000 ... Reach Financial's Risk and Decision Science team consists of a group of Data Scientists and ...

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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 are popular job titles related to Credit Risk Data Science jobs in New York? For Credit Risk Data Science jobs in New York, the most frequently searched job titles are:
What job categories do people searching Credit Risk Data Science jobs in New York look for? The top searched job categories for Credit Risk Data Science jobs in New York are:
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Credit Risk Data Science jobs near you
Credit Risk Data Capabilities, Manager

Credit Risk Data Capabilities, Manager

Fiserv, Inc.

New York, NY • On-site

$120K - $198K/yr

Full-time

This job post has expired 2 days ago. Applications are no longer accepted.

Fiserv rating

7.6

Company rating: 7.6 out of 10

Based on 94 frontline employees who took The Breakroom Quiz

110th of 146 rated financial services

Job description

Calling all innovators - find your future at Fiserv.
We're Fiserv, a global leader in Fintech and payments, and we move money and information in a way that moves the world. We connect financial institutions, corporations, merchants and consumers to one another millions of times a day - quickly, reliably, and securely. Any time you swipe your credit card, pay through a mobile app, or withdraw money from the bank, we're involved. If you want to make an impact on a global scale, come make a difference at Fiserv.
Job Title
Credit Risk Data Capabilities, Manager
What does a successful Credit Risk Data Capabilities Manager do at Fiserv?
As a Credit Risk Data Capabilities Manager, you will play a key role in advancing alternative lending for small businesses, driving growth and empowering merchants with faster, smarter lending solutions.
Working on Clover Capital, Fiserv's fast-growing product, you'll leverage Artificial Intelligence, machine learning, and open banking APIs to enhance risk assessment and automate credit decisioning. Your innovative contributions will ensure a scalable and automated risk framework that balances growth with strong risk controls.
What you will do:
  • Design and implement underwriting strategies for small business lending, integrating traditional and alternative data sources.
  • Utilize various data sources, including banking transaction data and cash flow analytics to improve and refine credit risk assessments.
  • Collaborate with external data vendors onboard, validate, and integrate data for enhanced risk evaluation.
  • Analyze external data sources to assess their predictive power and impact on credit risk models, partnering with data science teams to refine risk models.
  • Develop frameworks to monitor the effectiveness and ROI of external data usage in underwriting decisions.

What you will need to have:
  • Bachelor's degree in Finance, Economics, Statistics, Data Science, or a related field, and/or equivalent military experience.
  • 4+ years of experience with data analysis tools such as SQL, Python or R.
  • 3+ years in credit risk analytics, underwriting strategy, or decision science within small business lending.
  • 3+ years working with external data providers like bank aggregators (Plaid, MX, Finicity), cash flow analytics, credit bureaus, or alternative data.

What would be great to have:
  • Master's degree.
  • Experience in fintech, alternative lending, or embedded finance platforms.
  • Knowledge of regulatory and compliance considerations related to external data use in underwriting.
  • Exposure to API integrations and data ingestion pipelines for external data sources.
  • A passion for innovative financial technology solutions and applying new data sources to solve complex credit risk challenges.
  • Strong analytical mindset with the ability to think critically and develop creative solutions for credit risk management.

Important info about this role:
  • We're better together. This role is fully on-site.
  • In order to be considered, you must be legally authorized to work in the U.S. without need for sponsorship now or in the future.
  • This is a full-time, direct-hire position, and no contract options for unsolicited agency submissions will be considered.

Salary Range
$120,000.00 - $198,000.00
These pay ranges apply to employees in New Jersey and New York. Pay ranges for employees in other states may differ.
It is unlawful to discriminate against a prospective employee due to the individual's status as a veteran.
For incentive eligible associates, the successful candidate is eligible for an annual incentive opportunity which may be delivered as a mix of cash bonus and equity awards in the Company's sole discretion.
Thank you for considering employment with Fiserv. Please:
  • Apply using your legal name
  • Complete the step-by-step profile and attach your resume (either is acceptable, both are preferable).

Our commitment to Equal Opportunity:
Fiserv is proud to be an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, gender, gender identity, sexual orientation, age, disability, protected veteran status, or any other category protected by law.
If you have a disability and require a reasonable accommodation in completing a job application or otherwise participating in the overall hiring process, please contact AskHR.US@fiserv.com. Please note our AskHR representatives do not have visibility to your application status. Current associates who require a workplace accommodation should refer to Fiserv's Disability Accommodation Policy for additional information.
Note to agencies:
Fiserv does not accept resume submissions from agencies outside of existing agreements. Please do not send resumes to Fiserv associates. Fiserv is not responsible for any fees associated with unsolicited resume submissions.
Warning about fake job posts:
Please be aware of fraudulent job postings that are not affiliated with Fiserv. Fraudulent job postings may be used by cyber criminals to target your personally identifiable information and/or to steal money or financial information. Any communications from a Fiserv representative will come from a legitimate Fiserv email address.

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