Lead Data Scientist, Deliveries & ACE
Lead Data Scientist, Deliveries & ACE
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1 Vacancy
Job Description
Get to know the Team
In the ACE (Deliveries Mart Omnicommerce) Data Science team you are at the core and center of Grabs delivery and omnicommerce business. We build and deploy AI/ML models to empower seamless user experiences across Grabs food ecosystem from meal deliveries to restaurant reservations. Our mission is to enhance user satisfaction achieve growth and improve platform efficiency by using data science to solve unique challenges in delivery demand forecasting and personalized dining experiences.
Get to know the role
We are looking for Lead data scientists who will manage their projects end-to-end from defining the problem space proposing scalable DS solutions implementing DS services and to conducting experiments and model enhancement. You will work with partners including Engineering analytics Product and independently to provide advanced data-driven solutions. You will report to the Senior Data Science Manager and be based onsite at Petaling Jaya Malaysia.
The Critical Tasks You Will Perform
- Extract Insights: Analyze massive datasets (geospatial behavioral transactional) to understand user shopping patterns improve user experiences for delivery and dine-out/Reserve services.
- Identify business opportunity and propose AI solutions to solve user problem and create growth:
- User Experience: Predict users shopping needs & shopping patterns shopping preference cancellation probability and Identify ways to improve our user experience by providing them most personalised recommendations improving service reliability
- Demand Forecasting: Predict meal delivery demand spikes and restaurant reservation trends.
- Demand Shaping: increase visibility to ensure we are shaping demand to meet supply to increase the network throughput and reduce unfulfilled demand
- Demand generation: allow smart targeting of different user segments for demand generation
- Build Iterate and Deploy: Build AI models to allow business. Refine models through A/B testing and production monitoring.
- Collaborate: Partner with product managers engineers analytics design and operations teams to grow solutions.
- Contribute to teams innovation and IP creation.
Qualifications :
What Essential Skills You Will Need
- Masters Degree or graduate with at least 5 years of experience in Machine Learning Statistics Applied Mathematics Computer Science Economics Operations Research or a related field
- Experience as a Data Scientist within the food delivery booking or e-commerce industries.
- Experience with machine learning deep learning data mining algorithmic foundations of optimization. Experience with machine learning framework (Tensorflow pytorch)
- Proficient in the following programming languages: Python Scala.
- Learner and willing to share knowledge with team members
- To foster collaboration with team members and articulate insights to partners.
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 lifes challenges.
- Balancing personal commitments and lifes 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.
Remote Work :
No
Employment Type :
Full-time
Employment Type
Full-time
