Associate Fraud Strategy Data Scientist (Hybrid)
Together We Talent<\/p>
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The ideal candidate is a curious, impact -driven professional who can dive into large datasets, design fraud detection strategies, and clearly communicate data -driven insights to technical and non -technical teams.
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Position Overview
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In this role, you’ll partner with the Fraud Risk Strategy team to design and refine fraud detection rules, support strategy development with data science models, and surface actionable insights using SQL, Python, Tableau, and large -scale datasets. You’ll also work cross -functionally with product and engineering to improve fraud mitigation capabilities and customer experience.
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Key Responsibilities
<\/h3>Design fraud detection and mitigation rules
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Build Python scripts and data science models to support risk strategies
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Analyze large datasets to identify fraud patterns and root causes
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Collaborate with engineering and product teams to strengthen fraud controls
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Develop dashboards and data visualizations using Tableau
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Guide execution of fraud strategy roadmaps
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Present findings and recommendations to leadership and cross -functional stakeholders
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Requirements<\/h3>Required Qualifications
<\/h3>Bachelor's degree in Data Analytics, Data Science, Statistics, Mathematics, or related field
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2 years max of professional experience in risk analytics, fraud detection, or online payments
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Advanced SQL skills and proficiency in Python (plus data science libraries)
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Strong experience with Tableau or similar data visualization tools
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Experience working with large datasets and deriving actionable insights
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Ability to communicate findings clearly across stakeholders and teams
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Preferred Skills & Bonus Experience
<\/h3>AWS, Quicksight, or cloud -based analytics platforms
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Experience working with fraud rule systems or ML models
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Understanding of fraud typologies or abuse detection
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Experience supporting investigations or product abuse cases
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Prior exposure to eCommerce, fintech, or online marketplaces
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Expected Outcomes (6–12 Months)
<\/h3>Collaborate on new fraud strategies based on emerging threats
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Deliver dashboards tracking KPIs and fraud loss metrics
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Deploy data -backed solutions that improve fraud controls while enhancing customer experience
<\/p><\/li>
Support risk mitigation efforts that reduce financial losses across the platform
<\/p><\/li><\/ul>
<\/div><\/span>
Design fraud detection and mitigation rules
<\/p><\/li>
Build Python scripts and data science models to support risk strategies
<\/p><\/li>
Analyze large datasets to identify fraud patterns and root causes
<\/p><\/li>
Collaborate with engineering and product teams to strengthen fraud controls
<\/p><\/li>
Develop dashboards and data visualizations using Tableau
<\/p><\/li>
Guide execution of fraud strategy roadmaps
<\/p><\/li>
Present findings and recommendations to leadership and cross -functional stakeholders
<\/p><\/li><\/ul>
<\/div><\/span>
Requirements<\/h3>Required Qualifications
<\/h3>Bachelor's degree in Data Analytics, Data Science, Statistics, Mathematics, or related field
<\/p><\/li>
2 years max of professional experience in risk analytics, fraud detection, or online payments
<\/p><\/li>
Advanced SQL skills and proficiency in Python (plus data science libraries)
<\/p><\/li>
Strong experience with Tableau or similar data visualization tools
<\/p><\/li>
Experience working with large datasets and deriving actionable insights
<\/p><\/li>
Ability to communicate findings clearly across stakeholders and teams
<\/p><\/li><\/ul>
Preferred Skills & Bonus Experience
<\/h3>AWS, Quicksight, or cloud -based analytics platforms
<\/p><\/li>
Experience working with fraud rule systems or ML models
<\/p><\/li>
Understanding of fraud typologies or abuse detection
<\/p><\/li>
Experience supporting investigations or product abuse cases
<\/p><\/li>
Prior exposure to eCommerce, fintech, or online marketplaces
<\/p><\/li><\/ul>
Expected Outcomes (6–12 Months)
<\/h3>Collaborate on new fraud strategies based on emerging threats
<\/p><\/li>
Deliver dashboards tracking KPIs and fraud loss metrics
<\/p><\/li>
Deploy data -backed solutions that improve fraud controls while enhancing customer experience
<\/p><\/li>
Support risk mitigation efforts that reduce financial losses across the platform
<\/p><\/li><\/ul>
<\/div><\/span>
<\/h3>
Bachelor's degree in Data Analytics, Data Science, Statistics, Mathematics, or related field
<\/p><\/li>2 years max of professional experience in risk analytics, fraud detection, or online payments
<\/p><\/li>Advanced SQL skills and proficiency in Python (plus data science libraries)
<\/p><\/li>Strong experience with Tableau or similar data visualization tools
<\/p><\/li>Experience working with large datasets and deriving actionable insights
<\/p><\/li>Ability to communicate findings clearly across stakeholders and teams
<\/p><\/li><\/ul>Preferred Skills & Bonus Experience
<\/h3>AWS, Quicksight, or cloud -based analytics platforms
<\/p><\/li>Experience working with fraud rule systems or ML models
<\/p><\/li>Understanding of fraud typologies or abuse detection
<\/p><\/li>Experience supporting investigations or product abuse cases
<\/p><\/li>Prior exposure to eCommerce, fintech, or online marketplaces
<\/p><\/li><\/ul>Expected Outcomes (6–12 Months)
<\/h3>Collaborate on new fraud strategies based on emerging threats
<\/p><\/li>Deliver dashboards tracking KPIs and fraud loss metrics
<\/p><\/li>Deploy data -backed solutions that improve fraud controls while enhancing customer experience
<\/p><\/li>Support risk mitigation efforts that reduce financial losses across the platform
<\/p><\/li><\/ul>
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