Data Scientist Team
Role details
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Tech stack
Job description
Team AdAdvice ensures that advertisers receive clear, trustworthy and impactful recommendations to improve campaign performance. Moving beyond rule based approaches, we aim to create advice that dynamically responds to shopper behaviour, campaign performance and product relevance. This requires strong modelling, experimentation and data understanding. Your work will help advertisers make better decisions, reduce wasted spend and reach their goals with confidence. Get to know Data Science What you do as Data Scientist in AdAdvice As a Data Scientist in the Advertiser Advice product, you play a pivotal role in how bol develops and scales intelligence behind our advertising recommendations. You will design and operationalize models that identify opportunities, predict impact and guide advertisers toward better campaign outcomes. Whether you are building models to optimize search term relevance or identifying data-driven recommendations that optimize campaign budgets and spend, your work directly influences advertiser success and platform growth. What you will work on
- Develop and productionize machine learning models that power keyword suggestions, placement advice, budget guidance and product recommendations.
- Set up and maintain the advice modelling framework, including feature engineering, training pipelines, model monitoring and versioning.
- Build and manage experimentation workflows, including A/B testing and causal measurement to validate advice impact.
- Translate business questions into data science problems and communicate insights clearly to engineers, analysts, PMs and marketing stakeholders.
- Collaborate directly with engineers to ship robust models to production and ensure reliability, explainability and performance over time.
- Nice to have: experience with LLMs and embeddings to support generative or model based advice logic in the future. Why you can make a difference
Requirements
You have at least 5 years of experience working as a data scientist, applying your skills to real world, production-oriented challenges. You are comfortable designing end to end model workflows, running experiments and driving modelling conversations with both technical and non-technical colleagues. You are expert at breaking down big problems into smaller, incremental tasks that bring value. You are strong in Python's data science stack, SQL and cloud-based ML tooling. Experience with advertising, ranking, recommendations or search is a plus. Most importantly, you enjoy building sustainable data products, challenging assumptions and working cross functionally to create impact.