Senior Data Analyst, Risk and Fraud | Hoboken, NJ, USA

Senior Data Analyst, Risk and Fraud

{"description": " Discover What's Possible at BetMGM

Ready to make your career legendary? Join us as we bring the magic of Vegas to our players. The BetMGM team has over 1,400 talented members, revolutionizing sports betting and online gaming in the United States and Canada. We're a brand with technology at our hearts and the most driven and focused talent in the business.

As a valued team member, we're committed to giving you the resources and support you need to thrive. Our benefits and perks include:

• Medical, Dental, Vision, Life, and Disability Insurance

• 401(k) with company match

• Pre-tax spending accounts including health care FSA and commuter savings

• Flexible paid time off

• Professional development reimbursement and ongoing skills training opportunities

• Employee resource groups

• Swag, ticket giveaways, and more!

At BetMGM, we recognize that every individual plays a meaningful role in our success. That's why we're committed to building a respectful, inclusive workplace. It's the strategy behind every win. By meeting people where they are, we create a culture of belonging where everyone can thrive and a workplace that reflects our values, our people, and our drive to win.

About the Role

As a Senior Data Analyst, Risk & Fraud, you will leverage data and analytical techniques to detect, investigate, and mitigate fraud and financial risk across the business. You will transform large, complex datasets into actionable insights that support real-time decision-making and long-term risk strategy.

This role partners closely with stakeholders across Fraud Operations, Payments, Risk, and Compliance to identify emerging threats, uncover patterns in user behavior, and enhance detection and prevention frameworks. You will play a key role in analyzing transactional activity, monitoring fraud trends, and driving data-informed improvements to controls and processes.

This is a fast-paced, high-impact environment where success is defined by your ability to translate data into clear, evidence-based recommendations that reduce risk and improve operational efficiency.

Responsibilities

• Analyze large-scale transactional and behavioral data using SQL to identify fraud patterns, emerging threats, and key risk signals across the customer lifecycle.

• Design and develop scalable analytics solutions and automations (e.g., Python, Streamlit - a plus) to support fraud detection, investigation workflows, and operational efficiency.

• Build and maintain dashboards and monitoring tools (e.g., Power BI) to track fraud, payments, and risk performance metrics, reducing manual investigative effort.

• Support the development and optimization of fraud detection strategies, rules, and risk indicators through data-driven analysis and testing.

• Perform deep-dive investigations into suspicious activity (e.g., multi-accounting, geolocation anomalies, payment abuse) to uncover fraud networks and inform mitigation strategies.

• Ensure data quality, integrity, and consistency across fraud and risk reporting through strong validation, documentation, and control processes.

• Partner closely with Fraud Operations, Payments, Risk, and Compliance teams to translate analytical findings into actionable insights and measurable process improvements.

• Communicate complex fraud trends and investigative findings clearly and effectively to both technical and non-technical stakeholders

Qualifications

• Bachelor's or Master's degree in a quantitative field (e.g., Statistics, Computer Science, Mathematics), or equivalent experience in data analytics within risk, fraud, or payments

• 3+ years of experience in data analysis within risk, fraud, payments, or a related domain

• Strong analytical skills with proficiency in SQL and experience with data visualization tools (e.g., Power BI)

• Experience working with Python for data analysis or automation (preferred)

• Experience analyzing transactional or behavioral data to identify trends, anomalies, or risk signals

• Excellent communication skills, with the ability to translate complex findings into clear, actionable insights for non-technical stakeholders

• Strong problem-solving mindset with a focus on continuous improvement

• Ability to work in a fast-paced environment, adapt to changing priorities, and deliver under tight deadlines

• Proficiency with Microsoft Excel and PowerPoint for analysis and presentation of findings

• Strong troubleshooting skills, with the ability to identify, investigate, and resolve data or process issues

• Naturally curious, with a proactive approach to solving business and risk-related problems

• Strong verbal reasoning and critical thinking skills

• Data-driven mindset, using quantitative analysis to inform decisions and recommendations

• Ability to understand stakeholder needs and translate them into effective analytical or technical solution