What You'll Do
- Lead Complex Data Analysis: Independently design, execute, and interpret complex data analyses on large datasets to uncover critical insights related to fraud detection, compliance effectiveness, and customer behavior.
- Develop Advanced Reporting & Dashboards: Design, develop, and automate sophisticated reports and interactive dashboards that provide clear, actionable intelligence to various business and technical teams.
- Drive Rule Enhancement & Optimization: Proactively identify opportunities to enhance and optimize our anti-fraud and compliance rules based on in-depth data analysis and a thorough understanding of evolving threats.
- Champion Data Quality & Integrity: Establish and promote best practices for data collection, validation, and integrity, ensuring the accuracy and reliability of our analytical outputs.
- Investigate Emerging Threats: Lead research and investigation into new and sophisticated geo-blocking bypass methodologies and fraud tactics, developing strategies for detection and mitigation.
- Design & Implement Analytical Solutions: Architect and implement end-to-end analytical solutions, including data pipelines, statistical models, and advanced querying techniques.
- Collaborate & Influence: Partner effectively with product, engineering, operations, and other business teams to understand their needs, translate them into analytical requirements, and present findings and recommendations with clarity and impact.
- Mentor & Guide: Provide mentorship and guidance to junior data analysts, fostering their technical and analytical growth and promoting a collaborative team environment.
- Contribute to Product Strategy: Leverage data insights to contribute to the strategic direction of our products, identifying opportunities for new features, improvements, and optimizations.
- Stay Current with Industry Trends: Continuously research and evaluate new data analytics tools, techniques, and industry best practices to ensure GeoComply remains at the forefront of data-driven innovation.
What You'll Bring
- Bachelor's degree or higher in Computer Science, Mathematics, Statistics, Economics, or a related quantitative field. Master's degree preferred.
- Minimum of 5+ years of progressive experience in data analysis, preferably with a focus on fraud detection, risk management, or a related domain.
- Expert-level proficiency in database technologies (SQL, NoSQL, data warehousing concepts) with the ability to write highly optimized and complex queries.
- Advanced programming skills in Python or R for data manipulation, statistical analysis, and automation are highly desirable. Experience with relevant data science libraries (e.g., Pandas, NumPy, Scikit-learn) is also highly desirable.
- Proven experience designing and implementing sophisticated data visualization solutions using tools like Tableau, Power BI, or similar.
- Strong understanding of statistical principles, data modeling techniques, and experimental design. Experience with machine learning concepts is a significant plus.
- Demonstrated ability to translate business questions into analytical frameworks and deliver actionable insights that drive measurable results.
- Excellent communication and presentation skills, with the ability to effectively communicate complex technical concepts to both technical and non-technical audiences.
- Strong problem-solving and critical-thinking skills with a proven ability to independently investigate and resolve complex data-related issues.
- Proven ability to work independently, manage multiple projects simultaneously, and prioritize effectively in a fast-paced environment.
- Experience mentoring and guiding junior team members.
- A proactive and strategic mindset with a passion for leveraging data to solve challenging problems and drive business value.
Bonus Points For:
- Experience in online gaming, financial services, or other high-risk/regulated industries.
- Deep understanding of specific anti-fraud techniques, technologies, and industry best practices.
- Experience with cloud-based data platforms (e.g., AWS, Azure, GCP) and big data technologies (e.g., Spark, Hadoop).
- Experience building and deploying statistical models or machine learning algorithms.
- Contributions to data analytics communities or open-source projects.
Why Join GeoComply:
- Hybrid working mode & Modern office at a prime location in District 1
- Professional development budget to support your growth
- 20 annual leave days, 5 sick leave days
- Premium health insurance (Bao Viet or Liberty)
- Social, unemployment, and health insurance contributions based on full salary
- Competitive salary package, 100% salary during the probation period
- Attractive bonuses (13th month, business performance, equity plans)
- Annual salary performance review
- Free parking
- Annual company trip & Year-end party
- Quarterly team-building activities
- In-office snacks and drinks (snacks, coffee, juice, milk, etc.)
- International working environment
- Weekly yoga classes in the office
Top Skills
What We Do
Founded in 2011, GeoComply provides fraud prevention and cybersecurity solutions that detect location fraud and help verify a user's true digital identity. Our award-winning products are based on the technologies developed for the highly regulated and complex U.S. online gaming and sports betting market. Beyond iGaming, GeoComply provides geolocation fraud detection solutions for streaming video broadcasters and the online banking, payments and cryptocurrency industries, building an impressive list of global customers including Amazon Prime Video, BBC, Akamai, Sightline, DraftKings, FanDuel and MGM.
The company’s software is installed on over 400 million devices worldwide and analyzes over 10 billion transactions a year, placing GeoComply in a unique position to identify and counter both current and newly emerging fraud threats.
Proven and refined over 10 years of development, GeoComply’s solutions incorporate location, device and identity intelligence along with advanced machine learning to detect and flag fraudulent activity. By integrating GeoComply’s solutions into their processes and risk engines, organizations are able to identify fraud earlier in a user’s engagement, better establish their true digital identity and empower digital trust