The day to day activities
The day to day will see you working on varied tasks and projects, a selection of projects could include:
- Working with product managers and product analysts to impact-size and prioritise product feature lists for our next development sprints
- Running data-driven research to uncover new insights to inform product strategy, operational initiatives or changes in existing product configurations
- Conducting independent analysis of marketplace issues identified in a specific market; delivering insights & recommendations to our ops teams to balance such issues
- Sharing a recent piece of analysis or details of a new product with the rest of the team to provide coaching to help with similar projects
- Presenting a strategic opportunity assessment & analysis to leadership
- Writing a playbook to be used by operations teams which provides a mental model and documentation to tackle common marketplace situations supported by qualitative and/or quantitative insights
- Working with local teams to plan and design experiments for demand, supply and market clearance levers (e.g. via changes in pricing, driver incentives, driver dispatch logic)
Qualifications
The must haves
- At least 2 years of relevant work experience (for example in Analytics, Business Intelligence, Government, Management Consulting, or strategy roles in a tech company)
- Strong analytical knowledge - Prior experience in handling large, complex, high velocity data; familiar with common statistical, analytical and ML techniques; willing to continue to learn/apply new techniques as required.
- Strong understanding of causal inference - Able to design and recommend the most suitable ways for obtaining causal effects, be it through A/B tests or inference from quasi-experimental set-ups
- Strong presentation skills - Ability to distill insights & articulate an actionable point of view to non-technical audiences; Comfortable presenting to senior stakeholders; Good command of storytelling and presentation techniques (e.g. slide making, data visualisation)
- Convincing meeting presence and strong stakeholder management / influencing skills - Ability to get buy-in and drive decisions within the space of a meeting
- Problem solving & can do attitude - willing to learn quickly and understand the root cause of problems; able to work with a multidisciplinary team to propose creative solutions
- Ability to handle multiple priorities and solve ambiguous problems that may evolve in scope or complexity
- Good understanding of SQL and R/Python to work with data, including common packages/libraries
- Willing to travel (subject to travel guidance by Grab)
Good to have
- Bachelor's or Master’s degree in Economics, Finance, Psychology, Anthropology, Sociology, Computer Science, Data Science or related fields.
- Interest and experience in real-world applications of data science and data analytics - such as NLP, ML, Network analysis, spatial, econometrics or time-series analysis.
- Prior experience in training data science models using common machine learning libraries.
- Prior experience in Product Management.
- Prior experience in an operations role in a ‘direct-to-consumer’, online business or startup
