Lead Data Scientist (Analytics) – Deliveries

Company Description

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.

Job Description

Get to Know The Team

The Deliveries Analytics team is the analytics and data powerhouse behind Grab’s fastest-growing segments: GrabFood, GrabMart. Here, innovation meets action. We’re not just a team; we’re trailblazers, committed to solving the most pressing challenges for our consumers, driver-partners, and merchant-partners leveraging data. From revolutionizing the consumer order experience to enhancing platform reliability, we strive to make Grab the first choice, every time.

Get to Know The Role

You will report to the Head of Analytics, ACE and you’ll have the unique opportunity to collaborate across disciplines (Product, Business, Engineering, Design, Data Science) to transform data into dynamic solutions. Your insights will directly contribute to developing groundbreaking products and initiatives, setting new benchmarks for excellence. This isn’t just any role; it’s a chance to make a tangible impact on millions of lives every day.

The Critical Tasks You Will Perform

• You will innovate: Propose cutting-edge product ideas by diving deep into data, addressing the most pressing customer challenges.
• You will illuminate: Use your mastery of data to uncover trends, decode anomalies, and tell compelling stories that inspire action.
• You will Influence: Collaborate with stakeholders to define key metrics and design experiments that shape the future of our products.
• You will drive impact: Drive significant improvements across our platforms, enhancing user experience, and contributing to our mission of excellence.

Qualifications

What Essential Skills You Will Need

• You have at least 6 years in data-related or quantitative fields, with experience within D2C or B2C context such as Marketplaces, ECommerce, OmniCommerce, Retail Marketing Analytics, etc.
• You have the ability to help solve complex problems, narrowing down multiple options into the best approach, and take ownership of open-ended ambiguous business problems. Propose novel solutions that go beyond common practice
• You are able influence across your team and cross-functional teams. You should also be able to effectively convince senior stakeholders.
• You have exceptional skills in data visualization and storytelling. You should be adept at creating intuitive and impactful dashboards using PowerBI or Tableau.
• You are fluent in SQL, Python, R, or other scripting/programming languages, you’re a problem-solver at heart. Your comfort with very large datasets and complex ETL processes sets you apart.

Additional Information

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.

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.