Job Description
Location: In office - Bali
About Us
TyrAds is a leading tech-driven loyalty and rewards platform that partners with businesses to create meaningful and rewarding experiences for their customers. With millions of users across our platforms, we specialize in innovative AdTech solutions powered by big data, machine learning, and deep learning technologies.
Our systems process over 10,000 events per second, delivering real-time insights at scale. We build seamless user experiences across web, Android, and iOS, while leveraging ML/AI to power personalization and advertising effectiveness.
We are a team of 90+ employees worldwide and growing, guided by values of transparency, ownership, learning from mistakes, and respect for diverse cultures. Our product development follows Agile methodologies with weekly releases and collaboration tools such as GitHub, Jira, and Slack.
The Data & Fraud Analyst (DFA) is a key member of our customer support team, responsible for processing, analyzing, and reporting on data from game publishers, advertisers, and end-users using our offerwall platform. This role requires advanced data analysis and root-cause troubleshooting to diagnose and resolve SDK integration challenges, track performance metrics, and enhance customer success. By leveraging technical expertise and a deep understanding of user experience, the DFA addresses data-related issues, such as reward tracking and fraud rejection logic, ensuring seamless offerwall integration across client platforms and our own products.
Education
Job Requirements
- Bachelor's degree in Computer Science, Information Technology, Data Analytics, or a related field (or equivalent work experience).
Technical Proficiency
- Basic/Intermediate proficiency in SQL and experience with data visualisation tools (e.g., Tableau, Power BI).
- Advanced Microsoft Excel skills.
- Familiarity with programming languages such as Python or R for data analysis and automation.
- Understanding of digital advertising metrics, including impressions, clicks, and conversion rates.
Analytical Skills
- Demonstrated expertise in analysing large datasets to detect trends, anomalies, and actionable insights.
- Strong attention to detail in identifying discrepancies and ensuring data accuracy.
- Experience designing and implementing fraud detection strategies using data-driven approaches.
Problem-Solving Skills:
- Ability to think critically and develop creative solutions to complex data challenges.
- Proficiency in troubleshooting issues related to data pipelines and system integrations.
- Capability to work independently and manage multiple priorities effectively
Collaboration And Communication
- Strong written and verbal communication skills, with the ability to present analytical findings to technical and non-technical stakeholders.
- Proven ability to collaborate with cross-functional teams to achieve shared objectives.
Job Responsibilities
Data Analysis and Reporting:
- Analyse and interpret complex datasets to identify patterns, anomalies, and trends related to user engagement, fraud detection, and reward fulfilment.
- Utilise tools such as SQL, Tableau, Excel, and Google Analytics to generate actionable insights and support decision-making processes.
- Develop and maintain dashboards to monitor key metrics, providing regular reports on campaign performance and system efficiency.
- Collaborate with stakeholders to ensure accurate data tracking and improve reward payout mechanisms by identifying and addressing discrepancies.
Fraud Detection And Prevention
- Design and implement data-driven strategies to detect and prevent fraudulent activity across the platform.
- Analyse fraud patterns to refine rejection logic and enhance system rules for fraud prevention.
- Work with internal teams to evaluate the effectiveness of fraud detection measures and recommend improvements.
System Optimisation
- Continuously review and improve data pipelines and integration processes to ensure seamless functionality of the offerwall platform.
- Identify opportunities for process optimization, including automation of data analysis and reporting tasks.
- Support product and engineering teams by providing insights and recommendations to enhance platform features and reduce potential vulnerabilities.
Cross-Functional Collaboration:
- Partner with product, engineering, and business teams to share analytical insights and contribute to the development of new features.
- Collaborate with advertisers and publishers to improve data accuracy and campaign performance.
- Participate in the testing and validation of new platform features or SDK updates to ensure data integrity and user experience quality.
Documentation and Knowledge Sharing:
- Develop and maintain comprehensive documentation for data analysis processes, fraud detection methodologies, and reporting frameworks.
- Create internal knowledge resources to support teams in understanding data trends and system behaviour.
- Provide training and guidance to internal teams on analytical tools and fraud prevention strategies.
