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

Senior Data Scientists - Artefact UK

Hiring Organisation
Artefact
Location
London Area, United Kingdom
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 ...

Data Scientist (Football Club)

Hiring Organisation
Singular Recruitment
Location
City of London, London, United Kingdom
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 ...

SAS Engineer - London and remote - 8 months+

Hiring Organisation
Octopus Computer Associates
Location
London, United Kingdom
Employment Type
Contract
Contract Rate
GBP Daily
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 ...

Machine Learning Engineer

Hiring Organisation
Sanderson Recruitment
Location
London, United Kingdom
Employment Type
Contract, Work From Home
Contract Rate
£700 - £750 per day
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 ...