Staff Applied AI Scientist, Decision Systems

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  "source_hash": "b2ebb813c5f8993d5072c667da79c7bad3b60373be2660e5b73666f0cb55dc74",
  "last_changed_at": "2026-05-29T07:08:50.480Z",
  "active_status": "active"
}

{
  "language": "en",
  "location": {
    "raw": "San Francisco, CA",
    "city": "San Francisco",
    "region": "CA",
    "country": "United States",
    "is_remote": false,
    "confidence": 0.9
  },
  "salary_max": 250000,
  "salary_min": 180000,
  "inferred_at": "2026-06-06T20:00:50.076Z",
  "launch_scope": {
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    "language": "en",
    "location": {
      "raw": "San Francisco, CA",
      "city": "San Francisco",
      "region": "CA",
      "country": "United States",
      "is_remote": false,
      "confidence": 0.9
    },
    "countries": [
      "United States"
    ]
  },
  "remote_policy": "hybrid",
  "salary_period": "year",
  "workplace_type": "hybrid",
  "salary_currency": "USD"
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{}

{
  "lists": [
    {
      "text": "What You Will Work On",
      "content": "\n<li>Designing and formalizing structured AI reasoning frameworks that translate credit policy, risk strategy, and operational heuristics into production ready decision logic.</li>\n<li>Defining multi layer decision hierarchies across underwriting, collections, fraud detection, pricing optimization, and sales routing workflows, including conflict resolution logic when signals disagree.</li>\n<li>Establishing structured output standards for agent based systems so AI recommendations are interpretable, consistent, and actionable.</li>\n<li>Designing confidence scoring methodologies for AI assisted decisions and calibrating routing thresholds across auto approve, escalation, human review, and decline paths.</li>\n<li>Optimizing trade offs across risk exposure, approval rates, speed to decision, unit economics, and operational capacity.</li>\n<li>Analyzing override behavior and feedback loops to refine decision logic and improve system performance over time.</li>\n<li>Building evaluation datasets to test reasoning quality prior to deployment and defining clear production acceptance criteria.</li>\n<li>Benchmarking performance across decision domains and establishing monitoring standards to detect drift, degradation, bias, or inconsistency in AI outputs.</li>\n<li>Partnering with Engineering and MLOps to ensure monitoring, reporting, and feedback mechanisms are embedded in production systems.</li>\n<li>Supporting governance, audit, and compliance documentation to ensure decisions are explainable and defensible in a regulated environment.</li>\n<li>Assessing potential bias and unintended impact across workflows and partnering with Risk, Compliance, and Legal on responsible deployment.</li>\n<li>Quantifying business impact across loss rates, recovery performance, operational cost per file, funnel conversion, and cycle time, and aligning decision systems with portfolio economics and strategic objectives.</li>\n"
    },
    {
      "text": "What This Role Is Not",
      "content": "\n<li>Ownership of API development, integration pipelines, or infrastructure.</li>\n<li>Primary responsibility for MLOps tooling or production orchestration code.</li>\n<li>An academic or purely research focused AI position.</li>\n<li>A general program management or governance only role disconnected from production impact.</li>\n"
    },
    {
      "text": "What You Bring",
      "content": "\n<li>Eight or more years of experience in applied data science, including at least three years working on AI enabled product systems. Experience in AI product systems is required.</li>\n<li>Demonstrated experience designing, calibrating, and validating production decision systems.</li>\n<li>Experience translating domain expertise into structured logic frameworks that can be deployed in operational environments.</li>\n<li>Strong foundation in statistics, probability, and decision theory.</li>\n<li>Experience evaluating and tuning model outputs, including large language model reasoning outputs.</li>\n<li>Experience working in regulated or risk sensitive environments preferred. Background in fintech, lending, financial services, or other high consequence decision environments strongly preferred.</li>\n<li>Master’s degree in Statistics, Applied Mathematics, Data Science, Economics, Computer Science, Engineering, or related quantitative discipline required. PhD preferred.</li>\n"
    },
    {
      "text": "Why Join The Team",
      "content": "\n<li>This role offers the opportunity to shape how AI makes decisions across an entire lending platform.</li>\n<li>The work directly influences portfolio performance, unit economics, and operational strategy.</li>\n<li>You will operate in a company that is intentionally building AI into its core workflows, not experimenting at the margins.</li>\n<li>The systems you design will be durable, measurable, explainable, and central to the company’s long term competitive advantage.</li>\n"
    },
    {
      "text": "We Offer",
      "content": "\n<li>Comprehensive medical, dental, and vision coverage with multiple plan options to support you and your family.</li>\n<li>A 401k retirement plan with company matching contributions to help you build long term financial security.</li>\n<li>Generous paid time off and paid holidays to support balance and flexibility.</li>\n<li>Company paid life insurance and disability coverage for additional protection and peace of mind.</li>\n<li>Flexible Spending Account and Health Savings Account options to maximize tax advantages.</li>\n<li>A Lifestyle Spending Account to support wellness and fitness related expenses.</li>\n<li>A professional development stipend to encourage continued learning and growth.</li>\n<li>An employee referral program that rewards you for helping us build a strong team.</li>\n<li>Company events and initiatives that foster collaboration, inclusion, and connection.</li>\n"
    }
  ],
  "country": "US",
  "createdAt": 1772129388904,
  "updatedAt": null,
  "categories": {
    "team": "Risk Management",
    "location": "San Francisco, CA",
    "department": "Risk Management & Analytics",
    "allLocations": [
      "San Francisco, CA",
      "San Diego, CA"
    ]
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  "salaryRange": {
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    "currency": "USD",
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