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HomeCompaniesMulliganfundingStaff Data Scientist, Credit Strategy

Staff Data Scientist, Credit Strategy

Mulliganfunding · San Francisco, CA · Hybrid · Active · $180,000–$250,000 / year · Lever

Job facts

FieldValue
CompanyMulliganfunding
TitleStaff Data Scientist, Credit Strategy
Normalized title-
Department / teamRisk Management & Analytics / Risk Management
LocationSan Francisco, CA, United States
Work modelHybrid / Hybrid
Employment type-
Salary$180,000–$250,000 / year
Statusactive
ATS providerLever
Posted / first seen2026-01-08 / 2026-05-29
Changed / last seen2026-05-29 / 2026-06-06

Related slices

PageWhat it containsOpen
Company jobsActive postings from Mulliganfunding.Open
Company breakdownsRole, location, ATS, and work model facets for this company.Open
ATS provider jobsActive postings observed through Lever.Open
Provider filtered searchThe same provider as a filtered job collection.Open
City jobsActive postings in San Francisco.Open
Department jobsActive postings in Risk Management & Analytics.Open
Work model jobsActive Hybrid postings.Open
Lifecycle eventsOpen, update, close, and reopen events for this posting.Open
Original postingCanonical source or apply URL captured from the ATS.Open

Linked records

CompanyMulliganfunding
Source4142c825-74ba-4aeb-9961-f0cb52d2f94b
ATS providerLever

Description

Headquartered in San Diego, Mulligan Funding serves as a leading provider of working capital (Up to $5M) to the small and medium-sized businesses that fuel our country. Since 2008, we have prided ourselves on our collaborative, innovative, and customer-focused approach. Enjoying a period of unprecedented growth, driven by the combination of cutting-edge technology, human touch, and unwavering integrity, we are looking to add to our people first culture, with highly motivated and results-oriented professionals, to push the limits of what’s possible while creating value for all of our partners. Mulligan Funding deploys a powerful combination of statistically grounded credit strategy and robust manual underwriting to deliver credit performance aligned with our risk appetite while providing an outstanding customer experience. The Staff Data Scientist, Credit Strategy is a key member of the Risk Management team, responsible for designing, deploying, and optimizing end-to-end credit strategies that balance growth, profitability, and credit risk. This role plays a critical part in maximizing credit conversion and customer lifetime value while ensuring portfolio performance remains within established loss tolerances. This position partners closely with Risk leadership, manual underwriting, Product, Engineering, and Data Science teams to build scalable, data-driven credit strategies that support sustainable growth and resilient portfolio construction. This role follows a hybrid work schedule with three days onsite and two days remote each week, with Mondays designated as a mandatory onsite day. Mulligan Funding is an Equal Opportunity Employer (EOE) and takes great pride in building a diverse work environment. Qualified applicants are considered for employment without regard to age, race, religion, gender, national origin, sexual orientation, disability or veteran status. You will: Design and deploy innovative approval, qualification, and segmentation strategies that maximize application approval rates while achieving credit loss targets Develop and maintain underwriting policies that define minimum acceptance criteria and policy declines for segments outside Mulligan’s risk appetite Create statistically grounded credit limit assignment frameworks that optimize lifetime customer value while managing downside risk Design pricing and interest rate strategies, including testing frameworks, to ensure adequate loss coverage, strong borrower selection, and high customer take-up rates Optimize data collection strategies by balancing the information value of data against customer friction and operational cost Partner closely with the manual underwriting team to build a hybrid risk framework that integrates analytical strategies with expert manual review, ensuring consistent execution and continuous feedback loops Collaborate with Product, Engineering, and Data Science teams to design and deploy scalable infrastructure that enables rapid iteration and refinement of credit strategies Establish robust portfolio monitoring and reporting processes to track approval rates, credit performance, and risk metrics against expectations Apply a thoughtful, forward-looking approach to portfolio construction to ensure assets are resilient across economic cycles and attractive to debt investors on a risk-adjusted basis Incorporate macroeconomic trends and forward-looking risk signals into credit strategy to ensure ongoing relevance in evolving market conditions Performs other duties as assigned You have: 5+ years of relevant experience in commercial risk data science and credit strategy within a fintech or banking environment At least 3–4 years of hands-on experience designing, calibrating, and managing credit strategies for Merchant Cash Advance (MCA) products; prior MCA credit strategy experience is required Strong experience overseeing model deployment, execution, and monitoring within a production environment; ML Ops experience is highly preferred Master’s degree in Data Science, Statistics, Economics, Finance, or a related quantitative discipline required We offer: Medical, vision, and dental benefits to support you and your family. Flexible Spending Accounts (FSA) for eligible healthcare and dependent care expenses. A 401(k) with matching contributions to help you plan for retirement. Paid time off, including sick leave, vacation, and holidays. Paid parental leave for growing families. A Lifestyle Spending Account (LSA) for athletic and wellness expenses. An employer-sponsored Life and AD&D policy, with options for additional coverage. A Learning Stipend for professional development activities. An Employee Assistance Program (EAP) and travel assistance services. Complimentary snacks and refreshments in the breakroom. A referral program that rewards you for bringing in top talent. Company events to connect, celebrate, and grow together.

Full job record

Job IDb383a456eb28800fac20fac0ae2cacf36db4c6a0
Org ID051f5f41-34d6-4972-b3b6-43e9b00a0a2e
Source ID4142c825-74ba-4aeb-9961-f0cb52d2f94b
Board ID4142c825-74ba-4aeb-9961-f0cb52d2f94b
Providerlever
Provider Job Key9141b3f4-6f26-4c26-b7be-6007241f1f22
TitleStaff Data Scientist, Credit Strategy
Normalized Title
Statusactive
Activeyes
Location TextSan Francisco, CA
DepartmentRisk Management & Analytics
TeamRisk Management
Employment Type
Workplace Typehybrid
Remote Policyhybrid
CountryUnited States
RegionCA
CitySan Francisco
Salary RawUSD 180000-250000 per-year-salary
Salary Min180,000
Salary Max250,000
Salary CurrencyUSD
Salary Periodyear
Source URLhttps://jobs.lever.co/mulliganfunding/9141b3f4-6f26-4c26-b7be-6007241f1f22
Apply URLhttps://jobs.lever.co/mulliganfunding/9141b3f4-6f26-4c26-b7be-6007241f1f22/apply
First Seen At2026-05-29 07:08:50Z
Last Seen At2026-06-06 20:00:50Z
Last Checked At2026-06-06 20:00:50Z
Last Changed At2026-05-29 07:08:50Z
Inactive At
Source Posted At2026-01-08 22:24:59Z
Source Updated At
Raw Payload Uris3://job-postings-prod-raw-590183727216/raw/provider=lever/board=mulliganfunding/date=2026-06-06/2026-06-06T20-00-49-435Z-364a7ae42736ba8d6338a80549d88eb58e263eccf5bc15d2cc8437c2fa8771a1.json
Event Fields
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  "active_status": "active"
}
Parsed Structured
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Extensions
{}
Native Structured
{
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      "text": "You will:",
      "content": "\n<li>Design and deploy innovative approval, qualification, and segmentation strategies that maximize application approval rates while achieving credit loss targets</li>\n<li>Develop and maintain underwriting policies that define minimum acceptance criteria and policy declines for segments outside Mulligan’s risk appetite</li>\n<li>Create statistically grounded credit limit assignment frameworks that optimize lifetime customer value while managing downside risk</li>\n<li>Design pricing and interest rate strategies, including testing frameworks, to ensure adequate loss coverage, strong borrower selection, and high customer take-up rates</li>\n<li>Optimize data collection strategies by balancing the information value of data against customer friction and operational cost</li>\n<li>Partner closely with the manual underwriting team to build a hybrid risk framework that integrates analytical strategies with expert manual review, ensuring consistent execution and continuous feedback loops</li>\n<li>Collaborate with Product, Engineering, and Data Science teams to design and deploy scalable infrastructure that enables rapid iteration and refinement of credit strategies</li>\n<li>Establish robust portfolio monitoring and reporting processes to track approval rates, credit performance, and risk metrics against expectations</li>\n<li>Apply a thoughtful, forward-looking approach to portfolio construction to ensure assets are resilient across economic cycles and attractive to debt investors on a risk-adjusted basis</li>\n<li>Incorporate macroeconomic trends and forward-looking risk signals into credit strategy to ensure ongoing relevance in evolving market conditions</li>\n<li>Performs other duties as assigned</li>\n"
    },
    {
      "text": "You have:",
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    },
    {
      "text": "We offer:",
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    }
  ],
  "country": "US",
  "createdAt": 1767911099651,
  "updatedAt": null,
  "categories": {
    "team": "Risk Management",
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    "department": "Risk Management & Analytics",
    "allLocations": [
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      "San Diego, CA"
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    "currency": "USD",
    "interval": "per-year-salary"
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