Data Scientist

• Build AI That Solves Real Problems: Design, develop, train, and evaluate machine learning and statistical models across a wide range of business challenges.
• Turn Messy Data Into Insights: Explore, analyse, and visualize complex datasets to uncover patterns that matter. Perform feature engineering, data preprocessing, and selection to maximize model performance.
• Push the Boundaries With GenAI & NLP: Design and implement solutions leveraging Large Language Models, Retrieval-Augmented Generation (RAG), and NLP techniques.
• Experiment Rigorously, Deploy Confidently: Collaborate with data engineers and platform teams to move models from notebook to production, monitor performance over time, and support continuous retraining and improvement.
• Work Directly With Clients: Collaborate with clients across Western Europe and the USA to understand their business challenges, frame problems as data science opportunities, and communicate findings clearly.
• Stay Ahead of the Curve: Keep up with the latest in AI/ML research, emerging techniques, and new tools.

• Programming Skills (Key Requirement): Strong programming skills in Python (e.g. scikit-learn, TensorFlow, PyTorch, pandas, NumPy, Hugging Face, LangChain). The ability to write clean, maintainable, and reproducible code is essential.
• Machine Learning: Demonstrated hands-on experience building, training, and evaluating ML models. Strong understanding of supervised and unsupervised learning techniques, model selection, hyperparameter tuning, and cross-validation.
• Statistics & Mathematics: Understanding of core statistical concepts, probability, and linear algebra.
• NLP & GenAI (Highly Valued): Experience with natural language processing, text analytics, large language models, prompt engineering, RAG architectures, or other GenAI techniques.
• Computer Vision (Nice to Have): Experience with image processing, object detection, visual reasoning, or satellite imagery analysis is an advantage.
• Data Handling: Proficiency in SQL and experience with data wrangling, cleaning, and transformation.
• Cloud & MLOps (Nice to Have): Experience with cloud platforms (preferably Azure: Databricks, Azure ML, Synapse) or similar services on AWS/GCP is an advantage.
• Professional Background: At least 2-3 years of professional experience in data science, machine learning, applied research, or similar analytical roles.
• Language Skills: English at B2 level or higher.

PwC is a global network of more than 370,000 professionals in 149 countries that turns challenges into opportunities. We create innovative solutions in audit, consulting, tax and technology, combining knowledge from all over the world.

Join PwC’s Data & AI team and help design and deliver the AI and machine learning solutions that drive real business impact. We’re growing quickly due to a strong pipeline of client work, and we’re hiring across multiple seniority levels - from junior to senior Data Scientists.

Python is the core skill we expect. Depending on your strengths, you may focus on machine learning, statistical modelling, NLP, computer vision, or GenAI. Many roles also include “full-solver” flexibility - contributing where needed, including experimentation, prototyping, deploying models, or working end-to-end on AI use cases using modern platforms (including Microsoft technologies where relevant).