Lead Data Analyst at Grab in Singapore, Singapore

companyDescription About Grab and Our Workplace Grab is Southeast Asia's leading superapp. From getting your favourite meals delivered to helping you manage your finances and getting around town hassle-free, we've got your back with everything. In Grab, purpose gives us joy and habits build excellence, while harnessing the power of Technology and AI to deliver the mission of driving Southeast Asia forward by economically empowering everyone, with heart, hunger, honour, and humility. jobDescription Get to Know the Team The Integrity team is dedicated to safeguarding our users on Grab. We use our datasets to address multiple challenges, from ensuring safety to preventing fraud. We are involved in the entire data lifecycle, including analyzing user behavior and product funnels, identifying anomalies, and developing detection and prevention modules for suspicious activities. If you're enthusiastic about solving complex problems that have a direct, real-world impact, we'd love to have you on board! Get to Know the Role Reporting to the Analytics Manager in the Integrity team (Trust, Identity & Safety), you will help analyze data to understand user behaviors, product funnels and identify potential risks on our platform. Your insights will guide strategies to safeguard our diverse user base from multiple types of fraud and risk. The Critical Tasks You Will Perform You will act as a subject matter expert in utilizing data to measure and analyze business/product performance across different markets and business lines. You will lead the identification of business/product issues and opportunities, uncovering insights and pinpointing growth areas, developing data-driven rules and strategies to address potential risks. You will collaborate with product and engineering teams to design and analyze experiments that guide key product decisions. You will conduct statistical analyses to ensure detection systems align with industry standards, refining policies, strategies, and controls. You will lead expert teams in rolling out effective products/services and expanding the data universe for richer insights and enhanced decision-making. You will build and maintain dashboards for all stakeholders to provide visibility of key metrics, patterns and detection efficiency You will collaborate across teams to address risks associated with Grab's products, processes, and payment methods, serving as a strategic partner in risk management decisions. qualifications What Essential Skills You Will Need At least 4 years of experience in data-related or quantitative fields. A Bachelor's Degree in disciplines such as Analytics, Statistics, Software, Mathematics, Economics, Computer Science, or Engineering. Proficiency in SQL, Presto, ETL, Power BI, Tableau, Python, and Excel. Experience with the application of experimentation and statistical techniques (such as hypothesis testing, probability distributions, regression, decision trees). Knowledge of data models, data mining, and segmentation techniques. Understanding of the risk management space in digital ecosystems. Proficiency in Gen AI/LLM's. additionalInformation Life at Grab We care about your well-being at Grab, here are some of the global benefits we offer: We have your back with Term Life Insurance and comprehensive Medical Insurance. With GrabFlex, create a benefits package that suits your needs and aspirations. Celebrate moments that matter in life with loved ones through Parental and Birthday leave, and give back to your communities through Love-all-Serve-all (LASA) volunteering leave We have a confidential Grabber Assistance Programme to guide and uplift you and your loved ones through life's challenges. Balancing personal commitments and life's demands are made easier with our FlexWork arrangements such as differentiated hours What We Stand For At Grab We are committed to building an inclusive and equitable workplace that provides equal opportunity for Grabbers to grow and perform at their best. We consider all candidates fairly and equally regardless of nationality, ethnicity, race, religion, age, gender, family commitments, physical and mental impairments or disabilities, and other attributes that make them unique.