Senior Data Analyst, Integral Ad Science

• Bachelor’s or Master’s degree in Data Science, Computer Science, Computer Engineering, Digital Forensics, Cyber Security, Telecommunications, Information Assurance, or a closely related field
• A minimum of 5+ years of experience in data analysis/data mining, preferably within the AdTech or digital fraud landscape
• Expertise in writing complex queries, building functions, procedures, and investigative analysis using SQL
• Familiarity with data analysis libraries (e.g., Pandas, NumPy) and experience using Jupyter notebooks for exploratory data analysis
• Experience with multi-billion record data sets in cloud databases; familiarity with platforms such as Databricks is a strong plus
• Exceptional analytical and creative problem-solving skills
• Excellent verbal and written communication skills with proven success in presenting complex data in an engaging manner
• A proactive approach to continuous improvement and documentation of innovative methodologies
• Demonstrated ability to work autonomously while thriving in a team environment
• Strong customer focus with a drive for operational excellence and accuracy in all deliverables

Desirable

• Integral Ad Science (IAS) is a global technology and data company that builds verification, optimization, and analytics solutions for the advertising industry, and we're looking for a Data Analyst
• As part of the IAS Threat Lab you’ll investigate digital advertising threats by driving research initiatives that shape industry best practices, with continuous monitoring to capture emerging trends
• This role and team will have extensive interaction with large data sets (we monitor hundreds of thousands of transactions per second and collect tens of billions of events each day)
• Threat Monitoring & Analysis:
• Continuously monitor the digital advertising ecosystem for emerging threats
• Analyze impression-level data to identify and investigate potential fraud trends and anomalies
• Continuously improve existing analytical techniques and tooling to reduce the time required to assess and mitigate emerging threats
• Research & Innovation:
• Lead focused research initiatives to produce specialized insight reports on data quality, fraud detection, and emerging threats
• Identify top customer concerns and common issues, guiding systematic improvements in product design and functionality
• Develop impactful detection leads to accelerate the response from threat identification to the implementation of mitigation strategies
• Technical Analysis & Reporting:
• Build and optimize complex SQL queries, including the creation of functions, procedures, sub-queries, temporary tables, and complex joins
• Utilize Python (with Pandas, NumPy, and Jupyter notebooks) to create analyses, models, algorithms, and interactive dashboards
• Analyze historical data and document detailed findings to provide transparency and auditability across data processes
• Cross-Functional Collaboration:
• Partner with product management, data science, development, and marketing teams to develop comprehensive research reports, thought leadership articles, blogs, and bulletins that translate complex data into compelling, strategic insights
• Process Improvement & Documentation:
• Maintain comprehensive documentation of models, algorithms, and methodologies to support internal and customer-facing auditability