Senior Data Scientist / ML Engineer (Forecasting) | NDA

GT was founded in 2019 by a former Apple, Nest, and Google executive. GT’s mission is to connect the world’s best talent with product careers offered by high-growth companies in the UK, USA, Canada, Germany, and the Netherlands. Our clients operate in industries like healthcare, life sciences, fintech, retail, e-commerce, finance and many more - giving our team exposure to real-world, high-impact projects. About the Role We’re looking for an AI/ML Engineer to join a UK-based client in the healthcare and pharmacy domain. The role focuses on forecasting and time-series modeling, developing solutions that directly improve operational efficiency. Project duration : 12 weeks (with possible extension). Start date : June 15 (flexible - part-time start possible). Project Details : The project focuses on developing a forecasting solution for a large healthcare network. It uses historical clinic and marketing data to predict clinic usage and staffing needs, helping optimize scheduling and resource allocation. The goal is to build a scalable, data-driven platform that improves operational efficiency. Responsibilities: Design, train, and deploy ML models for time-series forecasting and related data tasks Build and maintain data pipelines using cloud-native tools (AWS, GCP, or Azure) Develop and optimize forecasting models (Prophet, ARIMA, LSTM, TimeGPT) Collaborate with data, product, and cloud engineers to deliver reliable, scalable solutions Participate in different stages of the project lifecycle - from discovery and PoC to production deployment, presenting your work to stakeholders Essential knowledge, skills & experience (must-have): 4+ years of experience in Machine Learning / Data Science Proven experience with forecasting / time-series modeling (Prophet, ARIMA/SARIMA, LSTM, TimeGPT, XGBoost or similar) Strong Python skills (Pandas, NumPy, scikit-learn, PyTorch) Experience with model deployment and production ML systems Familiarity with data preprocessing and feature engineering for time-series data Familiarity with cloud environments (Azure, AWS, or GCP) Version control (Git) and SQL Advanced English level Nice-to-have: Experience with Generative AI / LLMs Experience with RAG pipelines Experience with vector databases (Weaviate, Milvus) Familiarity with LLM evaluation frameworks (e.g. DeepEval) Soft Skills Strong sense of ownership and accountability Proactive attitude and ability to work independently Clear and confident communication with both tech and non-tech stakeholders Comfortable working in ambiguity and helping define requirements Strategic thinking and focus on business impact Team player Interview Steps GT interview with Recruiter Technical interview Final interview