Risk Management & Fraud Jobs

Introduction to Lazada

At Lazada, we want to make a positive impact by accelerating the progress of Southeast Asia through commerce and technology. As a part of the Alibaba family, we believe in empowering all aspiring entrepreneurs by making it easy to do business anywhere. Our ecosystem of brands, sellers and customers in the region aims to transform the way businesses run so our customers lead better lives. We believe we can better achieve that with a great team. If you are bold and can be your authentic self, let's explore ways of shaping the future together.

Team introduction:

The Lazada Security and Enterprise Intelligence department is responsible for protecting the eCommerce activities of over 560 million consumers, more than 155,000 sellers (merchants), and the 3,000 brands on Lazada’s growing ecosystem. We are increasing our investment in business security and significantly expanding our team. This is an exciting opportunity to be part of and shape the future of a strategic group within Lazada.

Key Responsibilities:

• Develop and communicate insights and recommended actions to stakeholders to manage risk by contributing towards machine learning models, rules and other detection systems.
• Perform data/statistical analysis to keep Fraud systems and processes at the cutting edge of fraud detection by identifying areas of potential fraud risk and/or potential opportunity to improve fraud policies, strategies and controls.
• Optimize fraud rules & algorithms to maintain strong fraud detection by rapidly identifying emerging fraud trends through data driven analysis and develop tactical/strategic fraud rules to address them.
• Work cross functionally on managing risk associated with Lazada products, processes methods.
• Envision and create alert mechanisms and automated outputs which keeps stakeholders aware of movement and deviations of key metrics.
• Build & maintain data pipelines required by upstream and downstream teams to manage risk related processes.
• Analysis of rich user and transaction data to surface patterns, trends, and bugs with regional on the processes and contribute to fraud prevention mechanisms.
• Be source of truth for risk metrics in the organization and own their logic as well as monitoring.
• Build & maintain dashboards for all stakeholders to provide visibility of key metrics, fraud patterns and detection efficiency.
• Play role of a data-driven strategic partner to risk related decisions in his/her area and is considered to be the subject matter expertise.
• Partner with Regional, Product and Business teams to conceive, design & monitor fraud risk strategies, create process and SOP in order to mitigate fraud risk in the most precise manner possible.
• Manage the reporting of key performance indicators; present analyses and findings to management to steer Security Risk Enterprise Intelligence, SREI’s strategic vision and mission.
• Analyze the effectiveness of existing fraud models and oversee the design, development, and management of new real-time fraud rules and models.

Key Qualifications & Skills

• At least 5 years of experience as a hands-on fraud analytics or response in related companies / industry.
• Business intelligence experience using tools such as Tableau, Qlik Sense and Excel.
• Strong project management skills, with experience in collaborating with different business functions and key stakeholders.
• Good understanding of the fraud space with hands-on knowledge of fraud, payments and risk.
• Working experience of any of the data analysis tools such as R, Python, SPSS, SAS etc.
• Strong experience in handling large scale unstructured data. Experience in SQL or other data handling tools, as well as ability to learn more advanced data.
• Understanding of Big data architecture and tools (Hadoop, Distributed SQL etc.)
• Proficient in RDBMS such as PostgresQL or SQL.
• Ability to make sound judgement calls independently when presented with difficult decisions, especially when only partial information is available
• Experience in the e-commerce industry a plus.
• Excellent written and verbal communication skills along with strong training skills.
• A technical degree in Computer Engineering, Information Technology, Data Sciences, Maths or related fields.
• Ability to take initiative in a fast-moving environment
• Experience with application of experimentation and statistical techniques (such as hypothesis testing, probability distributions, regression, decision trees etc.)