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Credit Risk Data Science Jobs (NOW HIRING)

NY · On-site

Sitting at the intersection of data science, credit risk, and product, you'll build the analytics and modelling foundations that inform underwriting, customer acquisition, retention, and portfolio ...

About the Role Flexcar is seeking a Risk Data Scientist to manage model-driven approaches to credit, accident, and fraud risk. We're looking for someone who can own the full lifecycle of our risk ...

$140K - $239K/yr

Partner with Data Science/Analytics to develop and validate credit scoring models, machine-learning underwriting tools, and early-warning indicators. * Set and manage credit risk appetite, exposure ...

About the Role Flexcar is seeking a Risk Data Scientist to manage model-driven approaches to credit, accident, and fraud risk. We're looking for someone who can own the full lifecycle of our risk ...

Credit Risk Analyst II

Boston, MA · On-site

$55K - $102K/yr

This role will leverage the analyst's proficiency in data, systems, and reporting tools combined with their practical knowledge of credit risk management principles. A successful analyst will be a ...

About the Role Flexcar is seeking a Risk Data Scientist to manage model-driven approaches to credit, accident, and fraud risk. We're looking for someone who can own the full lifecycle of our risk ...

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

... data to proactively identify emerging fraud and credit risk trends and propose innovative control strategies. * Collaborate closely with coworkers in the Risk Data Science, Risk, and Ops teams.

Credit Risk Analyst

$102K - $140K/yr

A Credit Risk Analyst at Prosper has the opportunity to utilize advanced analytical skills to ... Partner with Data Science, Product, Engineering and other partner teams to implement credit and ...

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 ...

Credit Risk Associate

Manhattan, NY · On-site

$160K - $200K/yr

Credit Risk Strategy owns these tradeoffs end to end. In this role, you will own or help build ... Engineering, Data Science, Risk Operations, Finance, Customer Experience, and Compliance. AI ...

Credit Risk Associate

New York, NY · On-site

$108K - $200K/yr

Credit Risk Strategy owns these tradeoffs end to end. In this role, you will own or help build ... Engineering, Data Science, Risk Operations, Finance, Customer Experience, and Compliance. AI ...

Showing results 41-60

Credit Risk Data Science information

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$37K

$113.9K

$197.5K

How much do credit risk data science jobs pay per year?

As of Sep 10, 2026, the average yearly pay for credit risk data science in the United States is $113,881.00, according to ZipRecruiter salary data. Most workers in this role earn between $82,500.00 and $140,500.00 per year, depending on experience, location, and employer.

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 skills and qualifications are needed to thrive as a credit risk data scientist?

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.
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Cities with the most Credit Risk Data Science job openings:

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Infographic showing various Credit Risk Data Science job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 83% Full Time, 12% Part Time, and 3% Contract. Highlights an 85% Physical, 3% Hybrid, and 12% Remote job distribution, with an average salary of $113,881 per year, or $54.8 per hour.

Data Science Manager (Credit)

NY • On-site

Other

Medical, Retirement

Posted 23 days ago


Key responsibilities

  • Develop credit scoring, affordability, and behavioural models to support underwriting, pricing, and collections

  • Design and run experiments to optimise approval rates, loss rates, and profitability

  • Partner with product squads to embed decision logic into real‑time systems


Job description

Who we are

Moniepoint is a global fintech building modern financial services for millions of people and businesses across high-growth markets. We provide payments, banking, credit, and financial management tools - reliable products that people and businesses use every day to run their lives, grow their companies, and move money safely.

Our mission is simple: to enable financial happiness for every African, everywhere. And this is day one. We’ve grown rapidly in Nigeria and the UK, and we’re now expanding our product, engineering, and analytics teams. Our work ranges from building financial infrastructure to designing intuitive customer experiences for emerging markets - solving real, meaningful problems at scale.

We onboard over a million new customers each month, process 100s of billions of dollars in payments annually, and support tens of millions of users across our ecosystem. Our teams operate in a fast‑paced, high‑impact environment alongside international leaders from companies like Glovo, Bolt, Monzo, Klarna, Checkout.com, and Tide. If you want to build our data science function from the ground up, work with one of Africa’s highest-scaling fintech data sets, and ship products that influence tens of millions of users, this is an exceptional time to join.

About the role

We’re looking for a hands‑on Spain‑based Data Science Manager to lead our consumer credit data science efforts in a high‑growth environment. This role is pivotal in building and scaling a team responsible for pricing, credit limit modelling, and production credit model deployment, with direct ownership of decisions that impact millions of customers.

You’ll work closely with our Consumer Credit, Product, and Engineering teams to shape how we assess and price risk, design credit products, and measure outcomes across the credit lifecycle. Sitting at the intersection of data science, credit risk, and product, you’ll build the analytics and modelling foundations that inform underwriting, customer acquisition, retention, and portfolio performance at scale.

Your day‑to‑day
  • Developing credit scoring, affordability, and behavioural models to support underwriting, pricing, and collections
  • Design and run experiments to optimise approval rates, loss rates, and profitability
  • Partner with product squads to embed decision logic into real‑time systems
  • Ensure data quality, compliance, and ethical use of models across all decisioning processes
  • Mentor product squads on best practices in experimentation and data‑driven decision making
  • Provide models to optimise outcomes in collections, churn management and user retention
We would love to hear from you if
  • You’re comfortable with Statistics – and have a Degree or qualifications in a quantitative field (Statistics, Mathematics, Engineering or similar)
  • You have +5 years of experience in data science, decision science, or risk analytics within financial services, including +2 years in management
  • Working knowledge of credit risk, consumer lending, and regulatory considerations
  • Proficiency in SQL and at least one modelling/programming language (Python, R)
  • Experience with A/B testing, machine learning, collections modelling and churn management
  • Ability to translate complex analyses into clear recommendations for business stakeholders
  • High ownership mindset and comfort working in fast‑paced, cross‑functional teams
What Moniepoint Can Offer You
  • The opportunity to drive financial inclusion and shape the future of the African financial ecosystem
  • The chance to work on innovative and impactful projects
  • A dynamic, diverse, and collaborative environment where every team member’s voice is recognised and valued
  • Flexible work arrangements
  • Continuous learning and career growth opportunities
  • Competitive salary, individual performance bonuses, and firm‑wide performance bonus
  • The company covered health insurance plans
  • Pension plans
What to expect in the hiring process
  • Introductory call with one of our recruiters
  • Initial interview with the Director of Data Science
  • Take‑home task (hands‑on coding or marketing modelling case study)
  • Business case interview with our Head of Marketing Strategy & Data
  • Live technical coding interview with the Director of Data Science
  • Culture & values interview (60 minutes) with the Director of Data Science

Moniepoint is an equal‑opportunity employer. We believe diversity makes us stronger and are committed to creating an inclusive environment for all employees and candidates.

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