Senior Data Scientist – Search & Recommendations

Responsibilities

Search Analytics & Insights → Analyze large-scale e-commerce search data to identify trends and improvement opportunities across search, ranking, recommendations, and personalization

Query & Ranking Analysis → Investigate search behavior, including zero results, query reformulation, abandonment, position bias, CTR, and relevance versus business trade-offs

KPI Measurement & Experimentation → Define and interpret search KPIs and rigorously evaluate online experiments across ranking, personalization, recommendations, and hybrid or vector search

Data & Metrics Development → Build end-to-end metrics layers using event-level data and server-side search logs, from raw tracking data to clear datasets and visualizations

Cross-Functional Analytical Leadership → Lead analytical initiatives and collaborate with Product, Data Science, MLOps, and ML/Search Engineering teams to improve product and business outcomes
Must Have

- Strong hands-on skills in SQL and Python, particularly Pandas, supported by solid statistical knowledge and the ability to create clear data visualizations

- Familiarity with the e-commerce search funnel and hands-on experience with query and ranking analysis, including zero results, reformulation, abandonment, position bias, CTR by position, and relevance versus business trade-offs

- Experience defining, tracking, and interpreting metrics such as CTR, PDP view rate, add-to-cart, conversion, revenue, and zero-results rate

- Experience designing and statistically evaluating ML/search experiments across ranking, personalization, and recommendations

- Proficiency with event-level data and server-side search logs, including building multidimensional metrics layers and end-to-end analytical solutions at large e-commerce scale

- Proven ability to collaborate with Product Owners, Data Scientists, MLOps, and ML/Search Engineers, lead senior-level initiatives, and deliver measurable product and business impact

- Proactive and curious approach to complex problems, with genuine enthusiasm for search, recommendations, ranking, personalization, and AI-powered product discovery

- Regular use of AI tools to improve productivity, automate or reduce repetitive work, support decision-making, and deliver higher-quality outcomes

- Ability to use AI tools responsibly by structuring effective prompts, critically validating outputs, understanding limitations, and taking ownership of the final result

Nice to Have

- Experience with GCP, distributed data systems, and analytical databases

- Familiarity with offline relevance evaluation metrics: NDCG, Recall@K, MRR and MAP

- Knowledge of information retrieval, recommender systems, or ranking models

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Enjoy our holistic benefits program that covers the four pillars that we believe come together to support our wellbeing, covering social, physical, emotional wellbeing, as well as work-life fusion.

- Physical Wellbeing: Our wellbeing program includes medical benefits, gym support, and personalised fitness options for an active lifestyle, complemented by team events and the Healthy Habits Club.

- Work-Life Fusion: In very dynamic industries such as IT, the line between our professional and personal lives can quickly become blurred. Having a one-size-fits-one approach gives us the flexibility to define the work-life dynamic that works for us.

- Emotional Wellbeing: We believe that to maintain our overall health, we need to invest in our mental wellbeing just as much as we do in our physical health, social connections or in achieving work-life balance.

- Social Wellbeing: As a growing community in a hybrid environment, we want to ens