Data Scientist

{
  "content_hash": "b81bebe91b3cef61ec02352de84387c7b45a07a9ec20bd24d2159d06a7e53dc3",
  "source_hash": "71909108c2ad80d070b0f019c700cdfaab48a41d2f8482f58e71fb7069a38713",
  "last_changed_at": "2026-05-30T06:01:33.064Z",
  "active_status": "active"
}

{
  "dedupe": null,
  "language": "en",
  "location": {
    "raw": "United States",
    "city": null,
    "region": null,
    "country": "United States",
    "is_remote": false,
    "confidence": 0.8
  },
  "salary_max": null,
  "salary_min": null,
  "inferred_at": "2026-06-20T10:52:47.526Z",
  "launch_scope": {
    "reason": "bamboohr_production_catalog",
    "included": true,
    "location": {
      "raw": "United States",
      "city": null,
      "region": null,
      "country": "United States",
      "is_remote": false,
      "confidence": 0.8
    },
    "countries": [
      "United States"
    ]
  },
  "remote_policy": null,
  "salary_period": null,
  "workplace_type": null,
  "salary_currency": null
}

{}

{
  "list_job": {
    "id": "115",
    "isRemote": null,
    "location": {
      "city": null,
      "state": null
    },
    "atsLocation": {
      "city": null,
      "state": null,
      "country": "United States",
      "province": null
    },
    "departmentId": "18525",
    "locationType": "1",
    "jobOpeningName": "Data Scientist",
    "departmentLabel": "Analytics",
    "employmentStatusLabel": "Full-Time"
  },
  "detail_errors": [],
  "detail_job_opening": {
    "location": {
      "city": null,
      "state": null,
      "postalCode": null,
      "addressCountry": null
    },
    "datePosted": "2026-03-30",
    "atsLocation": {
      "city": null,
      "state": null,
      "country": "United States",
      "countryId": "1"
    },
    "description": "<p>Founded in 1999, WorldWinner develops and operates competitive games of skill with real cash prizes under the WorldWinner consumer brand and in partnership with leading Sports Gaming Entertainment company FanDuel under the FanDuel Faceoff name.</p>\n<p> </p>\n<p>WorldWinner is the most recognized and trusted skill games technology platform and brand for players who want to Play to Win. We bring games to the world that inspire people to play for more. With over 20 challenging games where the outcome is dependent on player skills versus chance across a content library spanning classic card games to casual favorites to retro arcade games, WorldWinner has something for every gamer. Backed by Platinum Equity and strategic investors, we are building the next phase of our platform on mobile and beyond.</p>\n<p><br></p>\n<p>We are seeking a <span style=\"font-weight: bold\">Data Scientist</span> to join our analytics organization and serve as the technical modeling engine behind our player experience, monetization, and growth strategies. This is a hands-on individual contributor role embedded in a tight-knit analytics team, working directly with the Director of Business Performance on problem framing, prioritization, and execution.</p>\n<p><br></p>\n<p><span style=\"font-size: 14pt\"><span style=\"font-weight: bold\">What You'll Work On</span></span></p>\n<p>You will own the modeling workstreams that sit at the core of how WorldWinner understands and serves its players. Initial scope includes:</p>\n<ul>\n<li><span style=\"font-weight: bold\">Fair matching algorithm</span> — modeling and improving skill-based player matching to create competitive, satisfying game experiences</li>\n<li><span style=\"font-weight: bold\">Skill ranking system</span> — developing and refining the rating framework that underpins player progression and matchmaking</li>\n<li><span style=\"font-weight: bold\">Predictive LTV</span> — building models that forecast player lifetime value to inform acquisition, targeting, and monetization decisions</li>\n</ul>\n<p><br></p>\n<p>As you grow into the role, your scope will expand to include:</p>\n<ul>\n<li><span style=\"font-weight: bold\">Churn prediction</span> — identifying at-risk players and surfacing actionable signals for retention intervention</li>\n<li><span style=\"font-weight: bold\">Mixed marketing model (MMM)</span> — measuring the incremental impact of marketing spend across channels</li>\n<li>Additional modeling projects driven by product and business priorities</li>\n</ul>\n<p><br></p>\n<p><span style=\"font-size: 14pt\"><span style=\"font-weight: bold\">How You'll Work</span></span></p>\n<p>This role is not a silo. You will work closely with the Director of Business Performance throughout the lifecycle of every project — from framing the business question and scoping the approach, to communicating progress, surfacing blockers early, and presenting findings to stakeholders. We move fast, operate with high trust, and expect regular two-way communication on what you're building and why.</p>\n<p><br></p>\n<p>You will be expected to represent the analytics function in cross-functional meetings — with product, marketing, and engineering — without needing translation. That means explaining model logic to non-technical audiences, translating business questions into analytical approaches, and advocating for data-driven decisions in rooms where not everyone speaks statistics.</p>\n<p><br></p>\n<p><span style=\"font-size: 14pt\"><span style=\"font-weight: bold\">What We're Looking For</span></span></p>\n<p><span style=\"font-size: 14pt\"><br></span></p>\n<p><span style=\"font-weight: bold\">Required</span></p>\n<ul>\n<li>4+ years of experience in applied data science, with a track record of shipping models that drove measurable business outcomes</li>\n<li>Experience owning models end-to-end; from problem framing and development through deployment, monitoring, and ongoing iteration in production</li>\n<li>Strong proficiency in Python for modeling, statistical analysis, and data manipulation</li>\n<li>Advanced SQL skills and comfort working directly with large-scale data warehouses (Redshift experience a plus)</li>\n<li>Experience building and validating predictive models — LTV, churn, propensity, recommendation, or ranking systems</li>\n<li>Demonstrated ability to communicate technical work clearly to non-technical stakeholders — in writing, in meetings, and in executive presentations</li>\n<li>Comfort working in a collaborative, fast-moving environment with regular check-ins and shared prioritization</li>\n<li>Gaming industry experience — mobile gaming, real-money gaming, skill gaming, social casino, or live-service products</li>\n</ul>\n<p><br></p>\n<p><span style=\"font-weight: bold\">Preferred</span></p>\n<ul>\n<li>Experience with matching algorithms, ELO/Glicko-style rating systems, or similar player ranking frameworks</li>\n<li>Background in marketing mix modeling or multi-touch attribution</li>\n<li>Experience deploying models using cloud ML platforms (e.g. AWS SageMaker, Google Vertex AI, Databricks ML, or similar)</li>\n<li>Familiarity with modern analytics and data tooling (e.g. Hex, notebooks, dbt, Airflow)</li>\n<li>Exposure to experimentation design and A/B testing methodology</li>\n</ul>\n<p><br></p>\n<p><span style=\"font-size: 14pt\"><span style=\"font-weight: bold\">What Makes Someone Successful Here</span></span></p>\n<p>The data scientists who struggle in this role are the ones who disappear and resurface with a model deck. The ones who thrive are curious, communicative, and collaborative — they share work early, ask questions before making assumptions, and care as much about the business outcome as the model performance metric. If you've been told your superpower is making complex ideas accessible, this is the right place.</p>\n<p><br></p>\n<p><span style=\"font-size: 14pt; font-weight: bold\">Benefits Information</span></p>\n<ul>\n<li>Exciting, creative, and fun industry where you can make a measurable impact.</li>\n<li>Collaborative and inclusive work environment.</li>\n<li>Comprehensive subsidized medical, dental, and vision coverage with paid parental leave options.</li>\n<li>5% company 401(k) match with immediate vesting.</li>\n<li>Generous time off and flexible hours to support work-life balance.</li>\n</ul>\n<p><br></p>\n<p><span style=\"font-size: 14pt; font-weight: bold\">Equal Employment Opportunity</span></p>\n<p>WorldWinner is an equal opportunity employer and does not discriminate against employees or applicants based on race, color, national origin, gender, sex, sexual orientation, pregnancy, gender identity or expression, disability, religion, age, genetic information, veteran status or any other characteristic protected by federal, state, or local law. We will make reasonable accommodations to known physical or mental limitations of a qualified applicant or employee with a disability unless the accommodation imposes an undue hardship on our operation or direct threat safety to the individual or others in the work environment. We also participate in the E-Verify program, a service of DHS and SSA.</p>",
    "compensation": null,
    "departmentId": "18525",
    "locationType": "1",
    "seekPromoted": false,
    "jobCategoryId": null,
    "jobOpeningName": "Data Scientist",
    "departmentLabel": "Analytics",
    "jobOpeningStatus": "Open",
    "minimumExperience": "Experienced",
    "jobOpeningShareUrl": "https://worldwinner.bamboohr.com/careers/115",
    "employmentStatusLabel": "Full-Time"
  }
}