Data Scientist (Product Analytics) - Financial Services
Grab is hiring a Data Scientist (Product Analytics) - Financial Services in Jakarta, Indonesia. Level rates it ; you can apply on Grab.
Level's read on this job
- Little AI ●○○○ is how Level rates this data scientist role: aI is not part of the work.
- The posting mentions Databricks and NLP among its tools and skills.
- Level classes it as a mid-level role.
- Grab has 436 other open roles on Level.
- Posted within the past two weeks.
AI in this role
About Grab and Our Workplace
Grab 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 Team
GrabFin Analytics team supports the GFin product and business organisations, across Payments, Lending, Insurance, and Kios. As a Senior Data Scientist (Analytics), you will be part of the Lending tech family where we strive to be the best FinTech company in the region. Our team is focused on understanding user experiences and partnering with Business, Product, Design, and Tech teams to achieve the right outcomes. We are integral to product development, from understanding user journeys with UX designers, to developing hypotheses, through to post-rollout optimisation.
Get to Know the Role
In this role, you'll partner closely with Product Managers to turn product and business questions into clear hypotheses, thoughtfully designed experiments, and actionable insights. You'll build a deep understanding of users—their needs, pain points, and behaviours—while keeping business goals in view. As a strategic analytics partner throughout the product development lifecycle, you'll support teams from early ideation through execution, helping shape product direction and prioritize features based on evidence and expected impact.
The Critical Tasks You Will Perform
- Partner with cross-functional teams to identify data requirements and design innovative analytical solutions or insights to address complex challenges effectively.
- Conduct in-depth analyses of operational data, including business/impact analysis and text analysis, to identify areas for improvement and process optimization.
- Develop dashboards to monitor the performance of Grab Support operations, support specialists, and the business overall.
- Utilize advanced statistical and machine learning techniques, such as quasi-experimental methods, NLP & LLM, to analyze large datasets and derive meaningful insights that drive business decisions, improve support performance, and mitigate risks.
- Stay up-to-date with industry trends, emerging technologies, and best practices in analytics and data science, leveraging this knowledge to enhance the organization's data-driven capabilities.
- Collaborate with data engineering teams to ensure data quality, integrity, and accessibility, while building data pipelines and infrastructure for analytics projects.
- Communicate complex analytical findings to all stakeholders, including senior management, through concise reports, presentations, and visualizations.
What Essential Skills You Will Need
- A minimum of Bachelor's degree in Analytics, Statistics, or Engineering or any related field.
- At least 2+ years of experience in Analytics, Business Intelligence, or Data Science roles, preferably in an Internet or "Direct-to-Consumer" company with large, complex, high-velocity data.
- Proficiency in Big Data technologies such as Spark, PySpark, and Databricks.
- Strong foundation in data query/manipulation using SQL and data visualization tools like Power BI.
- Experience in Snowflake and multidimensional modeling .
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 life's challenges.
- Balancing personal commitments and life's 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.
How we rate this
Data Scientist (Product Analytics) - Financial Services at Grab rates 32 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Pay
- Typical data scientist job
- $167k
This posting doesn't list pay. Use the typical data scientist figure when pay comes up. See data scientist jobs
Questions you could be asked
- What NLP problem have you worked on, and how did you measure whether it actually worked?
- Walk me through how you've used Databricks in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: NLP and Databricks. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
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