Data Scientist

Singapore, Singapore

Job Description


Company DescriptionAbout Grab and Our WorkplaceGrab 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.Get to Know the TeamOur Business & Transaction Platform Data Science team uses data science to drive business growth and efficiency. We utilise the latest techniques in Computer Vision, Natural Language Processing and machine learning to solve complex challenges. Our work involves developing advanced algorithms and creating models to manage content and transform data into actionable insights to drive business growth and create value for our merchant partners and consumers.Get to Know the RoleAs a Data Scientist in the Business & Transaction Platform Data Science team, you will report into the Senior Data Science Manager and work hybrid in Singapore. You will dive deep into big datasets, develop efficient algorithms, and deploy solutions. If you are passionate about solving complex issues that drive innovation and impact our business operations, we\'re interested in you!The Critical Tasks You Will Perform

  • You will prepare large datasets for model building and training.
  • You will develop efficient and scalable deep learning algorithms.
  • You will evaluate algorithm performance on text and image datasets.
  • You will deploy machine learning solutions to production platforms.
  • You will stay updated with the latest research in Large Language Models (LLM), Generalised AI (GenAI), Natural Language Processing (NLP), and Computer Vision (CV).
  • You will stay up-to-date and understand the latest research and developments in advanced AI fields and contribute to the team\'s innovation and intellectual property creation.
QualificationsWhat Skills You Will Need
  • You are proficient in Python with good programming practices and have experience with deep learning frameworks like TensorFlow or PyTorch.
  • You are knowledgeable in the following areas: Large Language Models (LLM), Computer Vision, NLP, or Search domains.
  • You can prepare large datasets for model training and evaluation.
  • You have skills in designing and implementing scalable machine learning algorithms.
  • You have experience deploying machine learning models to production environments.
Additional InformationLife at GrabWe 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 GrabWe 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.

Grab

Beware of fraud agents! do not pay money to get a job

MNCJobz.com will not be responsible for any payment made to a third-party. All Terms of Use are applicable.


Related Jobs

Job Detail

  • Job Id
    JD1461843
  • Industry
    Not mentioned
  • Total Positions
    1
  • Job Type:
    Full Time
  • Salary:
    Not mentioned
  • Employment Status
    Permanent
  • Job Location
    Singapore, Singapore
  • Education
    Not mentioned