GoTo Group

Data Scientist

• Own the end-to-end modelling and estimation behind promotion optimisation — elasticity, heterogeneous treatment effects, budget-constrained allocation, and incrementality — from problem framing to production.
• Advance our causal inference stack: experiment and quasi-experiment design (geo/switchback tests, holdouts, diff-in-diff, synthetic control), debiasing observational data, and variance reduction — raising the bar on experimentation rigor across the team.
• Design and productionize heterogeneous treatment effect (uplift) models at scale (tens of millions of users), with honest offline evaluation (uplift/Qini curves, policy-value estimation).
• Formulate and solve budget-constrained allocation under fairness and dynamic business constraints — from LP/MILP to greedy or Lagrangian methods where they scale better.
• Mentor and technically guide a team of data scientists; set standards for model evaluation, documentation, and scientific review.
• Partner with business to turn model outputs into budget decisions, and communicate tradeoffs (subsidy efficiency vs. growth) clearly.

Principal Data Scientist – RPL

• Translate complex business challenges into well-defined technical problems solvable with data, statistics, and machine learning.
• Collaborate with product managers, engineers, and business stakeholders to build and scale data science solutions that power pricing across ride-hailing, food delivery and logistics
• Own the full ML lifecycle—from ideation and research to model development, pipeline implementation, deployment, experimentation, and driving measurable business outcomes.
• Improve the efficiency of our dynamic pricing system using techniques from econometrics, causal inference and simulation
• Design and interpret experiments to measure model impact, working with analysts and product teams to ensure rigorous evaluation and clear success metrics.
• Monitor and evaluate model performance, identifying areas for improvement and proposing solutions
• Communicate insights, trade-offs, and technical decisions effectively to cross-functional stakeholders, and operate with a high degree of autonomy in ambiguous problem spaces.

Senior Manager, Data Scientist – Pricing

• Collect and validate data from various sources to train our LLM.
• Analyze, review, and accurately label text data based on predefined guidelines.
• Ensure the consistency and quality of labeled data by following established protocols.
• Provide feedback on labeling guidelines and suggest improvements.
• Work closely with data science and engineering teams to meet project goals.
• Participate in daily standups and collaborate on projects.

Principal Data Scientist – RPL

Senior Manager, Data Scientist – Pricing

Data Scientist Intern