Senior Data Scientist (Deliveries & ACE)
Senior Data Scientist (Deliveries & ACE)
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Job Description
Get to Know the Team
The Deliveries & ACE Data Science team is at the heart of Grabs delivery and omnicommerce business. We create deploy and refine AI/ ML models to enrich the user experience across Grabs food ecosystemfrom meal deliveries to restaurant reservations. We are committed to enhancing user satisfaction promoting growth and optimising platform efficiency by solving unique challenges in delivery demand forecasting and personalised dining experiences.
Get to Know the Role
As a Data Scientist specialising in Deliveries and Dineout/ Reserve vertical you will report into the Senior Data Science Manager and work onsite in Grab One North Singapore office. You will help leverage data and AI to solve realworld challenges and drive impactful decisions. You will span advanced analytics machine learning model development and collaboration with crossfunctional teams to enhance the delivery and diningout experience for our users.
The Critical Tasks You Will Perform
- You will analyse largescale datasets (geospatial behavioural transactional) to uncover actionable insights about user shopping behaviours and patterns within delivery and dineout/ reserve services.
- You will use AI to forecast shopping needs preferences and cancellation probabilities improving personalised recommendations and enhancing service reliability.
- You will predict spikes in delivery demand and trends in restaurant reservations using advanced machine learning models.
- You will optimize visibility strategies to match user demand with supply ensuring efficient network performance and reducing instances of unfulfilled orders.
- You will enable smart targeting of distinct user segments to drive demand generation efforts.
- You will design test and deploy AI models refining them through A/B testing and monitoring their realtime performance.
- You will work with product managers engineers analysts designers and operations teams to scale and implement impactful solutions across the platform.
- You will contribute to the advancement of the team by driving innovation and creating intellectual property in AI/ ML space for deliveries and omnicommerce.
Qualifications :
What Essential Skills You Will Need
- You have a Master Degree in Machine Learning Statistics Applied Mathematics Computer Science Economics Operations Research or a related field
- You have at least 3 years of experience analysing largescale datasets to extract business insights (e.g. geospatial behavioural and transactional data).
- You have knowledge in machine learning deep learning optimization algorithms and data mining techniques. Familiarity with ML frameworks like TensorFlow or PyTorch is essential for building and refining predictive models.
- You have experience in finetuning LLM models and developing use cases based on LLM (e.g. for recommendation systems or user personalization).
- You are competent in Python or Scala to design and implement machine learning pipelines.
- You can forecast shape and generate demand using AIpowered strategies within delivery booking or ecommerce verticals.
- You have experience applying AI solutions to realworld problems in deliveries booking industries or ecommerce applications.
Additional Information :
Life at Grab
We care about your wellbeing 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 LoveallServeall (LASA) volunteering leave
- We have a confidential Grabber Assistance Programme to guide and uplift you and your loved ones through lifes 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.
Remote Work :
No
Employment Type :
Fulltime
Employment Type
Full-time
