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On Call Data Scientist Risk Jobs (NOW HIRING)

Aequor

Data Scientist

Basking Ridge, NJ · Hybrid

The candidate will have direct accountability to build and productionize data science models and AI/ML tools allowing for proactive risk monitoring, pattern detection and predictive analytics. This ...

Booz Allen Hamilton, Inc.

Data Scientist

Alexandria, VA · On-site

Data Scientist The Opportunity: In this role, you will apply data science techniques and methods ... risk, and develop courses of action. Employ expert judgment, adaptable methodologies, repeatable ...

Booz Allen Hamilton

Data Scientist

Alexandria, VA · On-site

Data Scientist The Opportunity: In this role, you will apply data science techniques and methods ... risk, and develop courses of action. Employ expert judgment, adaptable methodologies, repeatable ...

fphny

Data Scientist

Queens, NY · Hybrid

$78K - $80K/yr

The Data Scientist will also work closely with unit members on efforts to identify and maintain a large set of risk indicators to optimize health risk identification among the student population.

Southern Company

Data Scientist

Birmingham, AL · On-site

Specifically, this position is responsible for supporting Commercial Operations through risk analysis, data modeling, custom tool development and data science/analytics solutions which requires a ...

Southern Company

Data Scientist

Birmingham, AL · On-site

Specifically, this position is responsible for supporting Commercial Operations through risk analysis, data modeling, custom tool development and data science/analytics solutions which requires a ...

Rich Data Co

Senior Data Scientist

San Jose, CA

Design,present& documentAI-basedinitiatives to our clients,typicallybanking and risk executives ... years of data science experience,ideally in credit riskor financial services. * Experience ...

Sidram Technologies

Data Scientist

Seattle, WA · On-site

Develop ML-based risk scoring models across multiple fraud and exception scenarios, replacing ... hands-on Data Science experience with a strong foundation in classical ML * Proficiency in ...

USAA

Data Scientist Senior

San Antonio, TX · On-site

Develops and deploys models within the Model Development Control (MDC) and Model Risk Management ... Serves as a mentor to junior data scientists in modeling, analytics, and computer science tasks.

Jaris

Data Scientist

Burlingame, CA · On-site

$95K - $140K/yr

We are seeking an experienced Data Scientist to own the identity verification and fraud monitoring ... Partner cross-functionally with Compliance, Risk Operations, and Engineering to translate risk ...

Fusion Risk Management

Senior Data Scientist

The Role We're looking for a full-stack, product-minded Senior Data Scientist to help build a new ... risk scoring, escalation prediction, and recovery time estimation that improve through feedback ...

Verse

Data Scientist

San Francisco, CA · On-site

$146K - $172K/yr

Built by an expert team of energy buyers, data scientists, and engineers, Verse enables faster, smarter energy decisions that reduce risk and lower energy costs. The Role Verse is seeking a Data ...

Verse

Data Scientist

San Francisco, CA

$146K - $172K/yr

Built by an expert team of energy buyers, data scientists, and engineers, Verse enables faster, smarter energy decisions that reduce risk and lower energy costs. The Role Verse is seeking a Data ...

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How much do on call data scientist risk jobs pay per year?

As of May 30, 2026, the average yearly pay for on call data scientist risk in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.
What are the most commonly searched types of Data Scientist Risk jobs? The most popular types of Data Scientist Risk jobs are:
On Call Data Scientist Risk jobs near you

Data Scientist - Credit & Risk

Divine Research Inc

San Francisco, CA • On-site

Full-time

Posted 20 days ago

Job description

Traditional credit was built for people who already have money. Requirements for credit history, collateral, and costly underwriting create insurmountable barriers for those who need capital most. Over 1.4 billion people lack access to credit. A vendor in Lagos earns cash daily but can't prove a steady income. A Colombian nurse with years of perfect informal repayments remains invisible to banks. Most lending systems spend a lot to guess who will repay, and yet so many who are creditworthy still can't get a loan.
We built an alternative called Credit. Since December 2024, it has issued over one million unsecured loans using stablecoins. People from around the world have used these loans to pay for things like groceries, medicine, and transportation. Backed by $6.6 million from Paradigm and Nascent, we're scaling a system that has already reached more than 900,000 unique borrowers. Help us take it to the next level.
About the role
We're looking for a data scientist to drive credit risk intelligence across Credit, our leading unsecured lending system. You'll own portfolio monitoring and reporting, research emerging risk trends, and transform borrower behavioral data into actionable guidance that shapes our credit strategy and roadmap.
While our engineering & research teams owns the underlying models, you'll be the person who makes sense of what they're telling us, tracking portfolio health, identifying issues early, and turning insights into clear recommendations for risk strategy and underwriting policy. Over time, this role may expand to drive broader product analytics across our suite of products.
This role is based in San Francisco, California. We work in a hybrid model, with the team in office 3 days per week.
Stack
  • Python
  • SQL
  • Grafana/Prometheus/Metabase
  • Blockchain data and indexing tools (Dune, Shovel)
Key responsibilities
  • Monitor credit risk models, including underwriting, loss forecasting, and fraud detection, and iterate based on observed portfolio performance
  • Design, build, and maintain scalable data pipelines, monitoring infrastructure, and dashboards to track portfolio health, user behavior, and key risk indicators
  • Partner with product, research, and engineering teams to define north star metrics and translate them into measurable, actionable credit and growth strategies
  • Design and analyze A/B tests, quasi-experiments, and causal inference studies to evaluate the impact of product and policy changes
  • Produce portfolio monitoring and investigative analyses, making recommendations based on findings
  • Translate complex quantitative findings into clear, compelling narratives for product, leadership, and cross-functional stakeholders
Requirements
  • 4+ years of experience in decision science, credit risk analytics, or a closely related quantitative role within fintech or consumer lending
  • Deep proficiency in Python and SQL; comfortable owning analyses end-to-end from raw data to recommendation
  • Strong understanding of credit risk modeling concepts, including PD/LGD modeling, scorecard development, reject inference, vintage analysis, and risk segmentation
  • Demonstrated experience monitoring credit risk metrics and portfolio performance, including loss forecasting and underwriting model improvement
  • Proven ability to influence and collaborate with cross-functional teams and senior stakeholders, with a track record of translating analytical findings into accessible, actionable insights
  • Experience designing and evaluating experiments (A/B tests, holdout groups, or causal inference frameworks) in a consumer product context
  • Comfortable with ambiguity and biased toward action; thrives with minimal oversight and brings strong problem-solving skills and sharp attention to detail
Nice to have
  • Experience building or maintaining large-scale data pipelines supporting B2C financial products
  • Familiarity with credit bureau data, cash flow underwriting, or alternative data sources in credit model development
  • Experience working in emerging markets, ideally on financial products serving everyday consumer needs (microfinance, BNPL, digital lending)
  • Strong understanding of DeFi protocol mechanics (lending, yield vaults, ERC4626) and experience with onchain data tooling (Dune, Shovel, Ponder, Goldsky or similar)
  • Exposure to regulatory frameworks relevant to consumer credit (FCRA, ECOA, or equivalent)

Divine Research is an equal opportunity employer.

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