Our Data Science team will be partnering with the product and engineering
teams to drive actionable data insights and solutions from some of the
Bangladesh's most interesting datasets. We are looking to work on every aspect
of the product - whether it's exploratory research to understand user
behaviour for drivers and customers, running experiments to optimize untapped
areas of growth, or developing machine learning models to mitigate fraud on
our platform. The perfect candidate will have an excellent quantitative
background, will be able to address abstract business and engineering problems
with extreme precision, and has the enthusiasm and initiative necessary to
deliver those answers in a fast paced and dynamic environment.
Tasks and Expectations from this role are as follows:
Behavioural
- Develop a deep behavioural understanding and intuition of our passengers and drivers based on econometric analysis, geo-spatial visualizations, user interviews, and cultural understanding of our relevant markets
- Translate these intuitions into actionable, creative insights that improve the passenger and driver experience
- Test and validate these insights via rapid experimentation and deployment
- Communicate analysis and insights to stakeholders, and work effectively with tech and product teams to translate validated insights into deployable products
User Trust
- Develop a deep behavioural understanding and intuition of our passengers and drivers, especially in the space of how they would violate our policies and game our systems
- Apply heuristics, machine learning and data mining algorithms to predict default rate, identify and take down those who violate our Terms of Services
- Test and validate these insights via rapid experimentation and deployment
- Manage and own the entire end to end lifecycle of designing models, working with Engineering for implementation, to maintenance and enforcement
- Generate multivariate statistical models to identify latent factors, preventive and pre-emptive capabilities that the trust framework requires
- Interface with business & operation teams to formulate solutions & product changes informed by your findings
- Own the credit scoring model: Responsible for the end-to-end cycle of model building, model deployment, model interpretation
- Own the credit portfolio management system and success metrics: Responsible for continual tracking and reporting of portfolio risk exposure
Machine learning
- Build, validate and deploy machine learning models (e.g. predictive, forecasting, clustering)
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Be the technical expert in the team, and guide the team on best practices
Deploy an online learning model where applicable
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Gain access to lot of structured data, and develop creative algorithms by mining that data
- Define hypotheses, develop and execute necessary tests, experiments, and analyses to prove or disprove them
- Contribute to team’s innovation and IP creation
Operations Research
- Identify and solve business-wide problems using a combination of Big data and Operations Research (OR) techniques
- Build, validate, test, and deploy models and algorithms using proven and experimental techniques
- Define hypotheses, develop and execute necessary tests, experiments, and analyses to prove or disprove them
- Develop creative algorithms by employing OR techniques
- Translate data speak to human speak by effectively conceptualizing analysis to team members and business stakeholders
Preferred Attributes
- Position and compensation commensurate on experience
- Course of study in Statistics, MS or PhD preferred
- Research mindset - ability to structure a project from idea to experimentation to prototype to implementation.
- Familiarity with technical tools for analysis - Python (with Pandas, etc.), R, SQL, STATA
- Programming experience a plus.
- Prior experience working with ridesharing data a major plus