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Senior Data Scientist (AI)
Описание вакансии
Текст:
TL;DR
Senior Data Scientist (AI) (Machine Learning, Recommendations, Generative AI): Owns end-to-end machine learning problems across recommendations, personalisation, customer modelling and predictive modelling with an accent on production delivery, offline evaluation and measurable customer or commercial impact. Focus on designing feature pipelines and inference workflows, running online experiments, monitoring model performance, and applying embeddings or other generative AI capabilities.
Location: London or Manchester, hybrid with 1–2 office days per week
Company
is a digital product company operating high-volume customer and commercial experiences.
What you will do
- Own machine learning problems, models and components end to end across recommendations, ranking, personalisation, customer modelling and predictive modelling.
- Identify high-value customer and business opportunities with Product, Engineering, MLOps, Commercial and Marketing stakeholders.
- Build, tune and improve modelling approaches using feature engineering, model selection and robust validation.
- Design offline evaluation and online experiments that connect model performance with customer and commercial outcomes.
- Design feature-generation pipelines, scoring logic and inference workflows, and support deployment, monitoring, retraining and drift management.
- Develop practical AI-powered features using prompts, embeddings and other generative AI techniques, while contributing to code quality, mentoring and technical practices.
Requirements
- Strong experience delivering machine learning solutions and owning models or substantial ML components.
- Strong Python and SQL skills, with experience writing tested, maintainable and reproducible production code.
- Experience with supervised machine learning, feature engineering, tuning, validation, evaluation and problem-specific metrics.
- Experience with online experimentation, production ML deployment, monitoring, retraining, data quality and model drift.
- Ability to make independent technical decisions, explain trade-offs and influence Product, Engineering and business stakeholders.
- Awareness of testing, privacy, fairness, security and responsible use of AI-assisted development tools.
Nice to have
- Experience with recommendation, ranking, personalisation, propensity, uplift or customer lifetime value modelling.
- Experience applying LLMs, embeddings or generative AI to product or Data Science features.
- Experience in B2C e-commerce, retail or another high-volume digital product environment.
- Experience with AWS, dbt, large-scale or near-real-time ML systems, and mentoring junior colleagues.
- Degree in Statistics, Mathematics, Economics, Computer Science or another quantitative discipline, or equivalent practical experience.
Culture & Benefits
- Hands-on senior individual-contributor role with significant technical and product ownership.
- Opportunity to work on ambiguous problems and influence product and business prioritisation through evidence.
- Collaboration across Data Science, Product, Engineering, MLOps, Commercial and Marketing.
- Hybrid working model based in London or Manchester with regular office collaboration.
Hiring process
- Initial recruiter screening.
- Hiring Manager Interview, Technical Screening and Technical Interview Follow-up.
- Final Round; the exact structure may be adjusted and communicated to candidates.