Data Scientist (Product Analytics) - Financial Services
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Job Description
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.
Requirements
Function: Analyst
Experience Level: Entry Level