4 of 4 Remote/Hybrid Time Series Forecasting Jobs in London

tasks, and presenting project updates to both internal and client stakeholders. Advanced Modelling : Proven ability to implement a range of complex models such as time-series forecasting, gradient boosting, clustering, NLP, and Bayesian inference. ML-Ops & Orchestration : Strong experience with MLOps tools for orchestration, experiment tracking, hyper ...

Advanced proficiency in Python , including Pandas, NumPy and scikit-learn. Statistical & Machine Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks such as Keras or PyTorch Model Deployment : Proven ability to productionise models, including building ...

programming 2. SAS SQL 3. SAS Enterprise Guide or SAS Studio Strong understanding of modelling concepts such as: 1. Regression (linear/logistic) 2. Time-series forecasting 3. Segmentation models 4. Risk, pricing, or predictive modelling Experience with model development life cycle (MDLC) - development, testing, validation, documentation ...

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 ...