Senior Data Analyst, Anti-spoofing Operation

ABOUT CLIENT

Our client is working on global products, revolutionizing how people and businesses use the internet to instill confidence in every online interaction

JOB DESCRIPTION

Lead and develop analytical initiatives to address fraud detection challenges, from problem definition through implementation, monitoring, and continuous optimization.
Spearhead strategic efforts to combat emerging fraud patterns and develop innovative detection approaches through data analysis, testing, and impact measurement.
Design and implement production-grade data pipelines, automated workflows, and advanced analytical frameworks using statistical methods, machine learning, and geospatial analysis.
Conduct in-depth analyses of complex fraud operations and develop behavioral analytics systems.
Translate technical findings into actionable recommendations for leadership, product teams, and engineering. Lead compliance analytics initiatives and define evaluation metrics for new features.
Provide technical guidance and mentorship, establish best practices, and contribute to hiring top talent in analytics.

JOB REQUIREMENT

A bachelor's degree in a quantitative field such as Computer Science, Statistics, Mathematics, Physics, or a related field is required. A master's degree is strongly preferred.
Applicants should have 5-7+ years of progressive experience in data analysis and data science, particularly with expertise in fraud detection, risk management, cybersecurity, or related analytical domains.
Candidates should have a proven track record of driving business impact through advanced analytics and strategic insights.
Expert-level proficiency in SQL with a deep understanding of query optimization, complex joins, window functions, and data warehousing concepts is required.
Advanced Python programming skills with production-quality code standards, and extensive experience with data science stack (Pandas, NumPy, Scikit-learn, Matplotlib/Seaborn) are a must.
Strong foundation in statistical analysis, hypothesis testing, experimental design, and causal inference methods is required.
Hands-on experience in building and deploying machine learning models (classification, clustering, anomaly detection, time series analysis) is essential.
Proficiency in modern data visualization and BI tools (Looker, Tableau, Power BI) with the ability to design executive-level dashboards.
Experience with version control (Git), collaborative development workflows, and analytical documentation is necessary.
Strong understanding of data architecture, ETL/ELT processes, and data modeling principles is a must.
Experience with Databricks and Spark SQL, along with proficiency in terminal commands and SSH for remote server management, is highly desirable.
Experience with cloud-based data platforms (AWS, Azure, GCP) and big data technologies is highly desirable.
Familiarity with geolocation technologies, device fingerprinting, or network analysis concepts is highly desirable.
Ability to formulate complex business problems into analytical frameworks and deliver actionable solutions is required.
A strong product sense with the ability to balance competing priorities and experience designing metrics, KPIs, and measurement frameworks for detection or risk systems is necessary.
Proven ability to work autonomously on ambiguous, high-impact problems with minimal supervision is essential.
Exceptional written and verbal communication skills with the ability to present complex technical concepts to diverse audiences is a must.
Experience in mentoring analysts, contributing to team capability development, and collaboration skills across technical and business functions is needed.
Comfortable challenging assumptions and advocating for data-driven approaches is required.
Domain expertise in regulated industries, especially online gaming, sports betting, fintech, or other high-risk/regulated industries with deep understanding of fraud patterns and compliance requirements, would be beneficial.
Specialized Fraud Knowledge in expertise is advantageous.
Advanced ML/AI experience. Familiarity with real-time systems, advanced analytics, research contributions, deep learning, and cybersecurity background is a bonus.

WHAT'S ON OFFER

Learning opportunities and personal development support
Comprehensive health insurance coverage
Competitive compensation package
Lucrative bonuses including 13th month, business performance, and share appreciation rights
Annual salary performance review
Flexibility with hybrid working arrangements and contemporary office in a prime location
Annual company trip and year-end celebration
Regular team-building activities
Access to in-office snacks and beverages
International workplace atmosphere
Weekly in-office yoga classes

CONTACT

PEGASI – IT Recruitment Consultancy | Email: recruit@pegasi.com.vn | Tel: +84 28 3622 8666
We are PEGASI – IT Recruitment Consultancy in Vietnam. If you are looking for new opportunity for your career path, kindly visit our website www.pegasi.com.vn for your reference. Thank you!

Job Summary

Company Type:

Product

Technical Skills:

Data Analyst, Data Engineering

Location:

Ho Chi Minh - Viet Nam

Working Policy:

Hybrid

Salary:

Negotiation

Job ID:

J01989

Status:

Close

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