Lead Data Scientist

This is a fully remote position, open to applicants in United Kingdom.

📋 Description

• Oversee the design and implementation of large-scale AI, machine learning, and advanced analytics solutions.

• Lead a team or function focused on data science or Data & AI.

• Establish and maintain best practices in applied data science and data-for-AI methodologies.

• Function as a consulting data architect for designing and implementing data science and data-for-AI frameworks.

• Design and utilize data services to meet enterprise analytical and AI needs, including governance metadata.

• Convert business challenges into analytical solutions while identifying opportunities for predictive modeling, optimization, and data-driven decision-making.

• Create, develop, and implement machine learning models.

• Design prompts for securely hosted AI models and utilize LLM analytical capabilities.

• Employ statistical methods and experimental techniques, such as hypothesis testing and A/B testing.

• Perform exploratory data analysis to assess data asset value and uncover patterns, trends, and key drivers.

• Engineer features and prepare datasets to enhance model performance and reliability.

• Assess and refine models using metrics, cross-validation, and tuning strategies.

• Ensure model explainability and interpretability, effectively communicating results to both technical and non-technical stakeholders.

• Design and implement MLOps practices, including model versioning, monitoring, and retraining.

• Collaborate with data engineers to access, prepare, and scale datasets on cloud platforms.

• Present insights and recommendations through data visualization and storytelling.

• Contribute to the design of analytics and AI solutions that emphasize business value.

• Engage with stakeholders and clients during the discovery, experimentation, and solution design phases.

⛳️ Requirements

• 10 years of experience in data-oriented enterprise technology delivery or architecture.

• 5 years of experience as a senior data scientist or engineer delivering data science, machine learning, or advanced analytics.

• 2 years of experience working with GCP data technologies.

• Proficiency in machine learning techniques including regression, classification, clustering, and time series analysis.

• Experience in statistical analysis and modeling with production deployments.

• Comprehensive understanding of the end-to-end ML lifecycle: data preparation, modeling, evaluation, deployment, and monitoring.

• Skills in model performance tuning and validation techniques.

• Proficiency in SQL and experience handling large datasets.

• Experience in AI metadata service design and engineering.

• Proven ability to lead data teams from design through iterative program delivery and team management.

• Strong capability to elicit, analyze, and document requirements and processes.

• Familiarity with applied data techniques including identification, pipelining/ETL, curation, chunking, modeling, data quality, cataloging, lineage, and package deployment.

• Hands-on experience with Agile methodologies and involvement in Agile ceremonies.

• Ability to work independently while leading a small, multidisciplinary team.

• Strong problem-solving skills and meticulous attention to detail.

• Capability to clearly communicate complex data opportunities, AI, and analytical concepts to business stakeholders up to the C-level.

• Bachelor’s or Master’s degree in Data Science, Computer Science, Mathematics, Statistics, or a related field.

• Preferred: experience with Generative AI, RAG, Agentic AI, banking, financial services, insurance, AI governance, metadata management, data cataloging, multi-cloud platforms, client-facing workshops, solution design, pre-sales, and relevant certifications.

• Proficiency in Python and SQL.

• Familiarity with GCP technologies such as Dataflow, Dataproc, BigQuery, Dataplex, Looker, Vertex AI, and Gemini.

• Familiarity with Azure technologies including ADF, Synapse, AzureML, Databricks, Purview, Power BI, AzureGPT, or Claude.

• Experience with CI/CD using Jira, Azure DevOps, and Git repositories.

🏝️ Benefits

• Commitment to learning and long-term career development.

• Open and collaborative workplace culture.

• Exposure to high-performance data platforms and cloud infrastructure.