Data Analyst

Essential functions

• Own fraud monitoring: design, build, and iterate dashboards.

• Run the reviews: perform scheduled reads of dashboards, triage anomalies, and flag emerging farming/cheat strategies not covered by current models.

• Report the intel: publish periodic anti-fraud reports with executive summaries.

• Validate patterns: deep-dive game telemetry to confirm suspected patterns and identify data signatures that distinguish them.

• Label at scale: conduct large-batch manual user reviews, deliver clean, reliable datasets for model training.

• Size the risk: estimate affected populations, economy, and severity; propose containment/mitigation priorities.

• Investigate incidents: handle false-positive appeals and external allegations; document findings, and recommend policy/model/data fixes.

Qualifications

• Advanced SQL Proficiency: Demonstrated expertise in writing complex queries, including joins, window functions, Common Table Expressions (CTEs), and aggregations, with a strong focus on query optimization.

• Data Analysis Programming: Professional experience using Python (preferred) or R for data analysis, automation, and manipulation using libraries such as Pandas and NumPy.

• Statistical & Analytical Expertise: Solid foundation in Exploratory Data Analysis (EDA), statistical inference, probability distributions, and hypothesis testing.

• Data Visualization: Hands-on experience building dashboards and reports using Tableau, Dash, or Plotly, as well as Python-based visualization libraries like Matplotlib or Seaborn.

• Data Infrastructure: Experience working with cloud data warehouses such as BigQuery, Snowflake, Redshift, or PostgreSQL.

• Technical Workflow: Proficiency in version control systems, specifically Git, GitHub, or GitLab, and experience using Jupyter Notebooks for exploratory work.

• Pattern Recognition: Practical experience in anomaly detection, outlier identification, and behavioral pattern analysis.

• Fraud Investigation Frameworks: Familiarity with event/telemetry data analysis, manual dataset preparation, and the development of risk-scoring frameworks.

• Clear executive writing and cross‑functional communication.

Would be a plus

• Video game literacy

• Anti‑cheat/fraud pattern recognition experience

• Graph analysis

We offer

• Opportunity to work on bleeding-edge projects

• Work with a highly motivated and dedicated team

• Competitive salary

• Flexible schedule

• Benefits package - medical insurance, sports

• Corporate social events

• Professional development opportunities

• Well-equipped office

About us

Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI, supported by profound expertise and ongoing investment in data, analytics, cloud & DevOps, application modernization and customer experience. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.