Associate Data Scientist - User Fraud

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{
  "lists": [
    {
      "text": "What You'll Do",
      "content": "<div>\n\n<li>\n<p>Investigate evolving fraud trends and consumption habits to enhance detection capabilities.</p>\n</li>\n<li>\n<p>Apply your expertise in quantitative analysis, data mining, and data presentation to help automate, optimize and understand key business problems and solutions.</p>\n</li>\n<li>\n<p>Build data and tooling to empower operational and exploratory data analysis while optimizing for speed, accuracy, and quality.</p>\n</li>\n<li>\n<p>Work closely with cross-functional teams of data and backend engineers, and product managers.</p>\n</li>\n<li>\n<p>Partner with a broad range of stakeholders across music, podcasts and audiobooks to consistently uphold platform integrity.</p>\n</li>\n\n</div>"
    },
    {
      "text": "Who You Are",
      "content": "<div>\n\n<li>\n<p>A Bachelor's degree in Data Science, CS, or another quantitative field.</p>\n</li>\n<li>\n<p>1+ years work experience with an emphasis on investigative data analysis, anomaly detection, and data pipelines.</p>\n</li>\n<li>\n<p>Deep understanding of data with expertise in data manipulation and design (SQL) and experience in Python.</p>\n</li>\n<li>\n<p>Strong analytical skills, with the ability to turn data into actionable insights and recommendations.</p>\n</li>\n<li>\n<p>Strong problem-solving skills, intellectual curiosity, and a proactive approach to identifying new opportunities for fraud detection.</p>\n</li>\n<li>\n<p>A continuous learner, excited by new technologies and able to pick up new tools and frameworks quickly.</p>\n</li>\n\n</div>"
    },
    {
      "text": "Where You'll Be",
      "content": "<div>This role is based in Toronto.</div>\n<div>&nbsp;</div>\n<div>We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home.&nbsp;</div>"
    }
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  "country": "CA",
  "createdAt": 1775126933531,
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    "team": "Platform",
    "location": "Toronto",
    "commitment": "Permanent",
    "department": "Data and Analytics",
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