Data Scientist (Economist)

Get to know our Team:

• The Economics team takes on some of the most challenging and fascinating problems in Payments, Transport, Logistics, and the space around. We apply both qualitative and quantitative techniques to ensure that we make a positive impact to our customers, drivers and merchants. We promote a culture where we enjoy raising the bar constantly for ourselves and others, and that strongly supports the freedom to explore and innovate.

Get to know the Role:

• We are constantly looking to deepen our understanding of our consumers, drivers and merchants to drive business growth and profitability via close collaboration with other regional and country teams.

• This role focuses on the mobility and deliveries businesses, but cross-vertical projects are common. These projects will more often than not require a combination of data analysis, strategic thinking and idea generation. 

The day-to-day activities:

• Develop a deep behavioural understanding of our passengers, drivers, and merchants based on econometric analysis, geo-spatial visualizations, user interviews, and cultural understanding of our business lines in regional markets.

• Translate these understandings into actionable, creative insights that either directly impact or guide internal decisions pertaining to business growth and profitability.

• Test and validate insights via rapid experimentation and deployment, effectively working with other operational, tech and product teams to translate validated insights into scaled-up, deployed products.

The must-haves:

• At least 2-3 years of work experience in Finance, Economics, Psychology, Anthropology, Sociology, Computer Science, or related fields.

• Effective communication skills and the ability to present complex subjects coherently to diverse audiences comprising generalists and specialists.

• Ability to quickly grasp the fundamentals of a variety of businesses through a strong understanding of economic principles.

• Solid foundation in data query/manipulation using SQL.

• Hands on skills using R or Python in implementation of data science techniques on vast data.

The good-to-haves:

• A balance of right-brain and left-brain competencies, spanning a keen appreciation of human behaviour (e.g. deep interests in economics, sociology, anthropology and/or psychology), to data-driven analysis (e.g. randomised control trials, econometric tools

• An eye for both detail and the bigger picture, including the awareness to know which to focus on at any given time given project requirements.