4 of 4 Remote Time Series Forecasting Jobs in London

validate machine learning and statistical models for prediction, classification, clustering, or optimization. Apply supervised and unsupervised learning techniques using libraries such as Scikit-learn, TensorFlow, or PyTorch. Implement NLP, time-series forecasting, or optimization algorithms based on project requirements. Evaluate models using appropriate metrics and perform hyperparameter tuning for optimal performance. Convert proof-of-concept models into More ❯

to improve customer engagement metrics Skills ? Relevant experience in Customer Marketing Data Science including applied statistics and machine learning techniques (supervised and unsupervised learning, natural language processing, Bayesian statistics, time-series forecasting, collaborative filtering etc) ? Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) ? Familiarity with cloud platforms (GCP, AWS More ❯

Jupyter Notebooks . Statistical & ML Modelling: Strong foundation in statistical analysis and proven experience applying a range of machine learning techniques to solve business problems (e.g., regression, classification, clustering, time-series forecasting). Practical experience with Keras or PyTorch is required. Full-Stack Deployment: Demonstrable experience taking models to production, including building and deploying APIs with FastAPI More ❯

. Data transformation & manipulation : experience with Airflow, DBT and Kubeflow Cloud: Experience with GCP and Vertex AI (developing ML services). Expertise: Solid understanding of computer science fundamentals and time-series forecasting. Machine Learning: Strong grasp of ML and deep learning algorithms (e.g. Logistic Regression, Random Forest, XGBoost, BERT, LSTM, NLP, Transfer Learning). Reasonable Adjustments: Respect and More ❯