Principal Data Scientist - Causal Uplift & Budget Optimizer

Gotogroup; Jakarta Pusat; On-site; IDR 700,000,000 - 1,200,000,000; Full time

Job summary

GoTo Group is seeking a Principal Data Scientist to lead causal inference and uplift modeling for our promotions across services in Indonesia. You will own the end-to-end modeling lifecycle, mentor senior data scientists, and partner with product and engineering to drive growth and efficiency.

You'll design scalable uplift estimators, experiment designs, and budget-constrained allocation strategies while ensuring rigorous evaluation and clear communication of tradeoffs to leadership.

Qualifications

• 8+ years in data science with at least 3+ years in causal inference or uplift modelling in production.
• Strong expertise in heterogeneous treatment effect estimation.
• Experience optimizing promotions and incentives with evolving constraints.

Responsibilities

• Lead end-to-end modeling and estimation for promotion optimization including elasticity and budget-constrained allocation.
• Advance causal inference stack with experimental and quasi-experimental designs.
• Mentor data scientists and align model outputs with business budget decisions.

Tools

Meta-learners

Causal forests

DR-learner

Deep uplift

Job description

GoTo Group is seeking a Principal Data Scientist to lead causal inference and uplift modeling for our promotions across services in Indonesia. You will own the end-to-end modeling lifecycle, mentor senior data scientists, and partner with product and engineering to drive growth and efficiency.

You'll design scalable uplift estimators, experiment designs, and budget-constrained allocation strategies while ensuring rigorous evaluation and clear communication of tradeoffs to leadership.