Lead Data Scientist (Analytics)
Lead Data Scientist (Analytics)
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Job Description
Get to Know the Team
As a UserCentric Analytics (UCA) team member your role involves understanding analyzing and predicting the behavior of users (passengers drivers and merchants). This knowledge is critical in driving user engagement strategies enhancing user experience and contributing to overall business growth.
Get to Know the Role
As a senior or lead data scientist we expect you to be an individual contributor who leads the project endtoend from gathering requirements and bridging the gap to building and deploying a model and delivering impact for various teams. The primary responsibilities for this role include building userlevel prediction models for Competitive Index and High Net Worth Individuals which require an advanced understanding of statistics and AI/machine learning. As a data scientist specializing in userlevel prediction models your role will be crucial in optimizing user engagement and retention which are key strategies for driving business growth and profitability. You will report to Data Analytics Manager and based in Jakarta office.
The Critical Tasks You Will Perform
- Develop and implement predictive models to understand and forecast user behavior and engagement. This involves utilizing various machine learning and AI as well as statistical modeling techniques.
- Analyze and interpret massive or sparse datasets of transactional behavioral and millions of user interactions on our platform to understand user behavior and trends that can inform business strategies.
- Continually improve userlevel models through iterative enhancements ensuring they remain effective and relevant.
- Ensure the scalability of models to handle larger datasets or more features.
- Collaborate crossfunctionally with software engineers product managers marketing and country teams to translate business needs into data solutions.
Qualifications :
What Essential Skills You Will Need
- A degree in Computer Science Software Engineering Mathematics Physics or other related fields.
- 4 to 5 years of experience in largescale Machine Learning systems with a background in Machine Learning Statistics Applied Mathematics Computer Science or a related field.
- Familiarity with the concept of MLOps Lifecycle which refers to the process of managing and automating the lifecycle of machine learning models including data preparation model training model evaluation and model serving.
- Proficiency in ML Modeling with ML Frameworks such as Tensorflow and PyTorch.
- Proficiency in Causal Inference or other statistical methods and Python.
- Handson experience with one or more big data processing frameworks such as Spark.
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.
- 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 :
Fulltime
Employment Type
Full-time
