Data Scientist, Integrity
Data Scientist, Integrity
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Job Description
Get to Know Our Team
The Grab Integrity team is dedicated to protecting the Grab platform from multiple types of fraud and safety incidents. Our team uses rich datasets ranging from payment risk prediction using sequence-based models to detecting money laundering with graph algorithms and ensuring platform safety. We research new methods to stay ahead of latest fraud tactics contributing to the creation of thoughtful and secure products.
Get to Know the Role:
Youll fight fraud by analysing transactional data developing and deploying machine learning models and collaborating with teams to ensure seamless integration of fraud detection systems. Youll help keep our platform safe and trustworthy.
Reporting to the Data Science Manager II this will be a Full-time role in Bangalore
The Critical Tasks You Will Perform:
- Collaborate with your team to understand and convert operational issues into data science problems aligning efforts with our strategic goals.
- Stay updated with the latest research and advancements in the field incorporating the latest models and techniques to address new fraud tactics.
- Handle data preparation and augmentation using multiple data types to create comprehensive datasets for model training.
- Train and improve machine learning models ensuring accuracy and efficiency in fraud detection through careful selection and tuning of algorithms. Types of algorithms the team work on include Graph Neural Networks Transformer/ Sequence models finetuned LLMs Boosted Trees
- Deploy models into production managing their performance and working with data scientists software engineers and product managers to ensure seamless integration and ongoing improvements.
Qualifications :
The Essential Skills You Will Need:
- Degree in computer science physics statistics or a related quantitative field.
- Proficiency in Python SQL and programming skills with familiarity with numeric libraries containers and modular software design
- 2 or more years of experience of standard machine learning libraries such as TensorFlow PyTorch XGBoost LightGBM and Scikit-learn
- Understand and some experience using traditional ML techniques like Boosted Trees and deep neural network architectures like CNNs RNNs Transformers.
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.
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.
#LI-DNI
Remote Work :
No
Employment Type :
Full-time
Employment Type
Full-time
