💼 Data & Analytics – Data Scientist
📆 6-Month Contract | 🌍 Primarily Remote | 💰 Inside IR35
📍 Location: Hybrid – mainly remote. Occasional client travel may be required (pre-approved and reimbursed by the client).
💷 Rate:
- £435 – £522 / day (Umbrella)
- (Inside IR35)
🚀 About the Role
We’re seeking a skilled Data Scientist to join our Data & Analytics team for a 6-month project focused on AI in Commercial Banking.
You’ll lead end-to-end data science activities from data collection and cleaning to analysis, modelling, and insight generation working closely with client teams to deliver actionable, AI-driven outcomes that power smarter business decisions.
🎯 Key Responsibilities
As a Data Scientist, you’ll:
🔹 Collect, clean, and preprocess structured and unstructured data from diverse internal and external sources.
🔹 Perform exploratory data analysis (EDA) to uncover patterns, trends, and anomalies.
🔹 Design and build data pipelines with engineering teams to produce model-ready datasets.
🔹 Apply feature engineering and selection techniques to enhance model accuracy and interpretability.
🔹 Develop and validate machine learning and statistical models for predictive, classification, clustering, or optimization tasks.
🔹 Implement supervised and unsupervised learning algorithms using Scikit-learn, TensorFlow, or PyTorch.
🔹 Apply advanced techniques such as NLP, time-series forecasting, and optimization algorithms when required.
🔹 Evaluate and fine-tune models with appropriate metrics and hyperparameter optimization.
🔹 Collaborate with MLOps and engineering teams to transition proof-of-concept models into production-grade solutions.
🧠 Experience & Skills Required
You’ll bring:
✅ Proven ability to translate model outputs into clear, actionable business insights through compelling data storytelling and visualization.
✅ Experience building dashboards and reports with Power BI, Tableau, or Python-based visualization tools.
✅ Strong communication skills to engage both technical and non-technical stakeholders.
✅ Experience working with business analysts, architects, and domain experts to define use cases and success metrics.
✅ Contribution to enterprise AI roadmaps and a passion for promoting best practices in analytics and modelling.
✅ Thorough documentation of methodologies, model logic, and validation results for audit and reproducibility.
✅ Familiarity with Agile environments, participating in sprint planning, stand-ups, and client showcases.
