Senior Data Scientist, Experimentation Platform

Company Description

About Grab and our workplace

Grab is Southeast Asia’s leading superapp. We are dedicated to improving the lives of millions of users across the region by providing them everyday services such as deliveries, mobility, financial services, enterprise services and others. More than that, we provide the opportunity for them to have a better life. And that aspiration starts inside Grab because we believe in a seamless blend of work and home life, making every aspect of life better for all.

Guided by The Grab Way, which spells out our mission, how we believe we can achieve it, and our operating principles—the 4Hs: Heart, Hunger, Honour and Humility—we work to create economic empowerment for the people of Southeast Asia. With our unwavering commitment to our values, we believe that we're more than a service provider; we're agents of positive change.

Job Description

Get to know our Team

Grab is Southeast Asia’s leading super-app. We provide everyday services such as deliveries, mobility, financial services, enterprise services and others to millions of users across the region. At the AI Automation Team, we build end-to-end automated ML/AI solutions to solve challenging problems in Grab’s marketplace. The problem space we are working on consists of adaptive experiments, embeddings, recommendations and large scale marketplace optimizations. We are looking for lead machine learning engineers to join the team to help us make that vision a reality by developing and refining cutting-edge ML and experiment platforms. 

Get to know the Role

This is a hands-on role focusing on developing sophisticated experimentation frameworks and optimization algorithms. You will design and implement statistical testing methodologies, create robust experimentation platforms, and develop stochastic optimization solutions that drive business impact across Grab's ecosystem.

The ideal candidate will have a strong background in statistical analysis, experimental design, and optimization algorithms, with proven experience in developing scalable experimentation frameworks and optimization solutions. Deep understanding of causal inference, hypothesis testing, and stochastic processes is essential.

The day-to-day activities

• Design and implement sophisticated automated experimentation design and analysis frameworks. 

• Create scalable statistical analysis pipelines for experiment evaluation and interpretation.

• Implement stochastic optimisation algorithms for sequential decision making to optimise marketplace efficiency and personalised targeting. 

• Collaborate with product teams to design rigorous experiments and interpret results.

• Guide teams on proper experimental design and optimization methodology.

• Create and maintain documentation for experimentation best practices.

• Mentor team members on optimisations, statistical concepts and experimental design.

Qualifications

The must-haves

• A degree in Statistics, Mathematics, Computer Science, or related quantitative field

• 5+ years of experience in experimentation, statistical analysis, and optimisation

• Strong background in A/B testing, multivariate testing, and experimental design

• Expertise in statistical methods including hypothesis testing, power analysis, and causal inference

• Strong programming skills in Python for statistical computing

• Experience with experimentation platforms and frameworks

• Solid understanding of statistical learning theory and optimization techniques

• Knowledge of multi-armed bandit algorithms and reinforcement learning

• Experience in analyzing large-scale experiments and drawing actionable insights

• Experience developing production level pipelines

• Experience in implementing optimisation algorithms (gradient-based, evolutionary, Bayesian)

The nice-to-haves

• A Masters or PhD in Statistics, Operations Research, or related fields

• Experience with bayesian optimization and probabilistic programming

• Knowledge of advanced causal inference methods

• Knowledge of Bayesian decision theory

• Experience with distributed computing for large-scale experimentation

• Familiarity with online learning algorithms

• Publication record in relevant conferences or journals

• Experience with experiment tracking tools (e.g., MLflow, Weights & Biases)

• Knowledge of Spark or Ray, familiar with real-time event processing

Additional Information

Benefits at Grab:

We care deeply about your well-being and are committed to supporting you every step of the way. Here are some of the global benefits we offer:

• Protect and provide for your loved ones with peace of mind, knowing we have your back with Term Life Insurance and comprehensive Medical Insurance.
• Craft a benefits package that suits your unique needs and aspirations with GrabFlex, because we believe in empowering you to thrive.
• Embrace the magic of new life and create lasting memories with your family through Maternity and Paternity Leave.
• Life can be overwhelming, but you're never alone. Our confidential Grabber Assistance Programme is here to guide and uplift you and your loved ones through life's challenges.
• Your well-being is our priority. Benefit from our holistic well-being initiatives through Wellbeing@Grab, including health programmes, informative webinars, and vibrant carnivals.
• Achieve a harmonious work-life balance with our FlexWork arrangements, allowing you to adapt and thrive in your personal and professional life.

We’ve got many different benefits hyper localised in each country. Speak to your recruiter during your interview to find out more.

What we stand for at Grab:

We are committed to building an inclusive and equitable workplace that enables diverse Grabbers to grow and perform at their best. As an equal opportunity employer, we consider all candidates fairly and equally regardless of nationality, ethnicity, religion, age, gender identity, sexual orientation, family commitments, physical and mental impairments or disabilities, and other attributes that make them unique. If you require accommodations to fully participate in the recruitment process, you are encouraged to include your request(s) when applying.

We deliver the greatest impact and ideas when we bring together diverse perspectives. It is what enables us to spread opportunities to Grabbers and our partners. It’s not a box-ticking exercise; it’s who we are.