Role: Lead Data Scientist
Location: London (3 days per week onsite)
Salary: £98,000 + Bonus
Start Date: ASAP
A leading AI-driven insights and analytics business is seeking a Lead Data Scientist to play a pivotal role in shaping the organisation’s data strategy. You’ll lead complex data science projects from inception to deployment while mentoring a growing team of analysts and data scientists.
This company combines qualitative research with quantitative data science to uncover the attitudes and behaviours driving customer decisions. The team leverages technology and AI to enhance, not replace, human creativity and insight.
Responsibilities
- Lead end-to-end execution of complex data science projects integrating statistical modelling, machine learning (ML), and deep learning (DL).
- Collaborate closely with cross-functional teams (product, engineering, business stakeholders) to deliver data-driven solutions.
- Design and conduct hypothesis testing (A/B and multivariate testing) and apply causal inference methodologies.
- Perform exploratory data analysis, feature engineering, and develop models across traditional statistical and deep learning architectures.
- Establish modelling frameworks with statistical quality control, detecting drift and decay.
- Drive best practices for model explainability (e.g., SHAP/LIME) and scalable ML systems (including generative AI, NLP, CV, and recommendation engines).
- Partner with engineering teams to ensure robust deployment and adherence to MLOps principles.
- Shape and consult on broader data strategy and infrastructure.
- Mentor and coach junior team members while staying ahead of emerging trends in AI and machine learning.
Requirements
- Degree in Statistics, Computer Science, or a related field.
- 5+ years in data science with at least 2 years leading teams.
- Proven success in production deployment of ML/LLM/NLP/CV models.
- Strong understanding of machine learning fundamentals, statistical inference, and model evaluation.
- Advanced proficiency in SQL (e.g., PostgreSQL, ELT/ETL) and Python (PyTorch, LightGBM, Scikit-learn).
- Experience with modern AI concepts: prompt engineering, embeddings, vector search, etc.
- Skilled in managing complex codebases (Git) and working with cloud platforms (GCP, AWS).
- Excellent analytical, communication, and organisational skills.
Desirable
- MS/PhD in a quantitative field.
- Experience with Vertex AI, Kubeflow Pipelines, DBT, or agentic AI frameworks.
- Knowledge of multimodal or meta-learning approaches.
- Background in statistical consulting (sampling design, power analysis, non-parametric testing).
- Publications or patents in major conferences (e.g., NeurIPS, ICML, KDD).
- Understanding of marketing, media, or creative strategy domains.