Senior Data Scientist - Ads
Team: Data Science - Food, Ads & Search
Location: Bengaluru
Commitment: Permanent
Workplace Type: hybrid
What You Will Do
- Build and scale data science solutions that power GoFood’s merchant growth products (bidding systems, growth packages, targeting/forecasting models).
- Own the full ML lifecycle end to end: ideation, modeling, pipeline development, deployment, and measurement of business impact.
- Design, run, and interpret experiments using A/B testing and quasi-experimental methods.
- Apply causal inference and optimisation techniques to improve spend efficiency and create merchant growth packages.
- Partner with product, engineering, and business teams to shape merchant growth strategy and deliver measurable merchant outcomes.
- Translate ambiguous merchant growth and advertising problems into clear technical solutions grounded in data and experimentation.
- Communicate technical decisions, insights, and trade-offs clearly to cross-functional stakeholders.
What You Will Need
- Bachelor’s or Master’s degree in a quantitative field (e.g., Computer Science, Statistics, ML) with 1-3 years of industry experience applying data science to real-world problems.
- Proficiency in Python and SQL, with hands-on experience working with large-scale datasets and cloud platforms (e.g. GCP, AWS, AliCloud, Tencent Cloud, Azure).
- Strong grounding in statistics, machine learning, and causal inference, with a track record of end-to-end problem solving rather than theoretical work.
- Ability to frame ambiguous product and business questions into structured, well-scoped technical problems.
- Strong communicator who can clearly explain insights, trade-offs, and decisions to both technical and non-technical audiences.
- Experience owning the full DS lifecycle: data exploration, modeling, pipeline development, experimentation, and impact measurement.
- Self-driven, collaborative, and eager to build innovative solutions that drive merchant growth at scale.
Bonus Point If You Have
- Practical experience with ad ranking, user targeting, price elasticity, pacing or bidding systems.
- Exposure to on-demand platforms or consumer internet businesses.
- Contributions to open-source projects or other public showcases of applied data-science work.
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