21 of 21 Time Series Forecasting Jobs in London

Senior/Lead Applied Data Scientist - Causal AI for Demand Forecasting Location: Offsite, London, United Kingdom Area of Interest Job Type Professional AI or Artificial Intelligence Job Id Location: Offsite, London, United Kingdom Area of Interest Engineer - Software Job Type Professional Technology Interest AI or Artificial Intelligence Job Id New Meet the Team The post-pandemic years have exposed … inherent biases and limitations in human-driven and statistical/Traditional ML-based forecasting approaches. Cisco wasn't immune and saw a sharp increase in backlogs, inventory levels, and supply chain costs. The Forecasting Data Science Team within Global Planning is solving this by using Causal AI to redefine Demand Forecasting and its Enterprise impact. We're … in the Process and Technology Innovation category. Your Impact You will bring your skills, experience, and innovation to play a significant role in shaping our Causal AI-based forecasting system to improve decision making and drive operational performance and efficiency across Cisco's Enterprise and Supply Chain functions. You Will Develop, evolve, and sustain key elements of the Causal More ❯

powerful customer insight product designed to help organisations better understand and maximise the value of their customer base. Responsibilities: Create scalable solutions to solve real-world challenges like demand forecasting, personalisation, and customer segmentation Translate business problems into data science use cases and deliver measurable outcomes Apply clustering, classification, regression, time series modelling, NLP, and deep learning. … Science, Artificial Intelligence, Mathematics, Statistics or related fields. Strong coding skills in Python and SQL Communication skills – able to translate complex insights into business value Strong experience with clustering, time-series forecasting, and regression techniques. Experience working end-to-end **Please note that this role does not offer visa sponsorship** How to Apply: Register your interest by More ❯

powerful customer insight product designed to help organisations better understand and maximise the value of their customer base. Responsibilities: Create scalable solutions to solve real-world challenges like demand forecasting, personalisation, and customer segmentation Translate business problems into data science use cases and deliver measurable outcomes Apply clustering, classification, regression, time series modelling, NLP, and deep learning. … Science, Artificial Intelligence, Mathematics, Statistics or related fields. Strong coding skills in Python and SQL Communication skills – able to translate complex insights into business value Strong experience with clustering, time-series forecasting, and regression techniques. Experience working end-to-end **Please note that this role does not offer visa sponsorship** How to Apply: Register your interest by More ❯

this including: Bayesian statistics and supervised learning to model conversion rates and revenue Scaled AI/ML with Tensorflow/Vertex AI to model a travelers propensity to book Time series forecasting As a part of the Science and Optimization team, we deliver through the full data product life-cycle: from prototyping to production development to A … Competitive compensation packages, stock options offered to every employee, Bonusly program to reward and recognize team wins and performance, plus employees can take up to 40 hours of paid time per year to volunteer and give back to the community Flexibility: Flexi-Friday benefit, hybrid or remote work options for most roles, time-zone friendly work hours with … and increase long-term growth, customer loyalty and profitability. Our customers include hotels, attractions and tourism boards, and they use the power of machine learning, data science and real-time traveler data in Sojerns products to build direct relationships with travelers across social, mobile and the web. Now, more than ever, our thousands of customers rely on Sojern to More ❯

feeds, market data, satellite imagery, and proprietary sourcesEnsure data quality, consistency, and reliability across heterogeneous data streams ML Development: Design and deploy models for pattern recognition, anomaly detection, and time-series forecastingContribute to model training, validation, and optimization processes Software Engineering: Develop production ML systems in Python on Google Cloud PlatformBuild and maintain APIs for data ingestion, model … Preferred Experience: Data orchestration tools (e.g. , Airflow, Prefect)Experience deploying, monitoring, and maintaining ML models in production environments (MLOps)Familiarity with big data technologies ( e.g. , Spark, Hadoop)Background in time-series analysis and forecastingExperience with data governance and security best practicesReal-time data streaming is a plus (Kafka, Beam, Flink)Experience with Kubernetes is a plusEnergy/ More ❯

feeds, market data, satellite imagery, and proprietary sourcesEnsure data quality, consistency, and reliability across heterogeneous data streams ML Development: Design and deploy models for pattern recognition, anomaly detection, and time-series forecastingContribute to model training, validation, and optimization processes Software Engineering: Develop production ML systems in Python on Google Cloud PlatformBuild and maintain APIs for data ingestion, model … Preferred Experience: Data orchestration tools (e.g. , Airflow, Prefect)Experience deploying, monitoring, and maintaining ML models in production environments (MLOps)Familiarity with big data technologies ( e.g. , Spark, Hadoop)Background in time-series analysis and forecastingExperience with data governance and security best practicesReal-time data streaming is a plus (Kafka, Beam, Flink)Experience with Kubernetes is a plusEnergy/ More ❯

Science, Engineering, or similar. Programming proficiency: Experience with Python and SQL for data analysis, manipulation, and basic modelling. Understanding of machine learning: Exposure to predictive modelling techniques, particularly in Time Series Forecasting, NLP, or Recommendation Systems. Data visualisation: Familiarity with Tableau, Power BI, or similar tools. Strong analytical and communication skills: Able to interpret complex data and 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 ❯

behavioural data previously unavailable. The Role Data Cleaning and Preparation: Collect, clean, and prepare large media datasets from various sources for analysis. Statistical Analysis: Use econometric techniques like regression, time series, and panel data analysis to explore relationships between media spend and outcomes. Model Validation and Interpretation: Evaluate model accuracy, interpret results, and communicate findings clearly to stakeholders. … and model accuracy. Your Experience and Skills Data Science: Proficiency in Python, R, SQL, including data manipulation, statistical modeling, and visualization. Econometrics: Experience with regression, panel data analysis, and time series forecasting. Media Industry Knowledge: Understanding of media landscape, ad formats, audience measurement, and KPIs. Communication Skills: Ability to explain complex concepts to non-technical stakeholders. Business Acumen More ❯

Data Cleaning and Preparation: Collect, clean, and prepare large media datasets from various sources (CRM, ad servers, audience panels) for analysis. Statistical Analysis: Utilise econometric techniques like regression analysis, time series modelling, and panel data analysis to identify relationships between media spend and business outcomes. Model Validation and Interpretation: Evaluate the accuracy and robustness of models, interpret results … and SQL including data manipulation, data imputation, statistical modelling, and visualisation libraries. Econometrics Background Useful: Expertise in statistical methods like linear regression, generalised linear models, panel data analysis, and time series forecasting. Media Industry Knowledge: Understanding of media landscape, ad formats, audience measurement, and industry KPIs. Communication Skills: Ability to clearly communicate complex statistical concepts and insights to More ❯

Data Cleaning and Preparation: Collect, clean, and prepare large media datasets from various sources (CRM, ad servers, audience panels) for analysis. Statistical Analysis: Utilise econometric techniques like regression analysis, time series modelling, and panel data analysis to identify relationships between media spend and business outcomes. Model Validation and Interpretation: Evaluate the accuracy and robustness of models, interpret results … and SQL including data manipulation, data imputation, statistical modelling, and visualisation libraries. Econometrics Background Useful: Expertise in statistical methods like linear regression, generalised linear models, panel data analysis, and time series forecasting. Media Industry Knowledge: Understanding of media landscape, ad formats, audience measurement, and industry KPIs. Communication Skills: Ability to clearly communicate complex statistical concepts and insights to More ❯

and leagues around the world Familiarity with a broad range of statistical techniques, such as regression modelling, Monte Carlo simulation, GLMs, mixed effects models, gradient boosting, ensemble modelling, and time series forecasting Interest in betting/prediction problems A flair for communicating statistical analyses to both technical and non-technical audiences Experience with SQL and relational databases … the betting industry A good understanding of the mechanics of betting markets Project management skills, including an ability to make sensible value judgements about where the team should spend time Experience producing readable, testable and maintainable code on a collaborative codebase A good knowledge of AWS (or a similar cloud platform) What we offer Half yearly bonus opportunities based More ❯

and that improve experience of over hundreds of millions of online shoppers. EU STEP brings together Supply Chain, Network Design, and Transportation Planning teams to improve end-to-end forecasting, network flow, planning, and execution. It also brings together our teams from across the business focused on our Operational Excellence pillars - Amazon Customer Excellence Systems (ACES), Learning, Quality, Service … as for other applications within Amazon Transportation Services, and impact the future of the Amazon delivery network. Current research and areas of work within our team include machine learning forecasting, planning systems and robust decision making on large networks, as well as uncertainty quantification, generative models on graphs and ml explainability, among others. We are looking for an Applied … Scientist with a strong academic background in the areas of machine learning, time series forecasting, and/or optimization. At Amazon, we strive to continue being the most customer-centric company on earth. To stay there and continue improving, we need exceptionally talented, bright, and driven people. If you'd like to help us build the place More ❯

s degree. Proficient in Python (core skill), with strong experience in SQL, AWS, and CI/CD pipelines Strong Data Science and Machine Learning fundamentals Strong experience with clustering, time-series forecasting, and regression techniques. **Please note that this role does not offer visa sponsorship** How to Apply: Register your interest by sending your CV to Emily More ❯

s degree. Proficient in Python (core skill), with strong experience in SQL, AWS, and CI/CD pipelines Strong Data Science and Machine Learning fundamentals Strong experience with clustering, time-series forecasting, and regression techniques. **Please note that this role does not offer visa sponsorship** How to Apply: Register your interest by sending your CV to Emily More ❯

understand and act on physical climate risk. You’ll define the ML strategy, shape a high-impact team, and deliver real-world innovation across generative AI, geospatial modelling, and time-series forecasting. Key Responsibilities Own and evolve the company’s AI & ML strategy in line with product and customer priorities Lead, mentor, and grow a high-performing team … AI tools for geospatial risk assessment Building models to project the impact of floods, cyclones, heat stress etc Leveraging satellite imagery and remote sensing for climate hazard detection Enhancing time-series forecasts to inform asset-level risk planning Combining simulation outputs with ML for hybrid physical + statistical modelling What We’re Looking For Proven leadership and strong … hands on experience Proven track record of deploying ML into production environments Depth in at least one of: generative AI, geospatial ML, computer vision, or forecasting Experience working with climate data (or similar) Excellent communication skills and cross-functional collaboration ability Experiene working in start ups/scale ups. Bonus Points Experience with satellite imagery or other Earth-observation More ❯

understand and act on physical climate risk. You’ll define the ML strategy, shape a high-impact team, and deliver real-world innovation across generative AI, geospatial modelling, and time-series forecasting. Key Responsibilities Own and evolve the company’s AI & ML strategy in line with product and customer priorities Lead, mentor, and grow a high-performing team … AI tools for geospatial risk assessment Building models to project the impact of floods, cyclones, heat stress etc Leveraging satellite imagery and remote sensing for climate hazard detection Enhancing time-series forecasts to inform asset-level risk planning Combining simulation outputs with ML for hybrid physical + statistical modelling What We’re Looking For Proven leadership and strong … hands on experience Proven track record of deploying ML into production environments Depth in at least one of: generative AI, geospatial ML, computer vision, or forecasting Experience working with climate data (or similar) Excellent communication skills and cross-functional collaboration ability Experiene working in start ups/scale ups. Bonus Points Experience with satellite imagery or other Earth-observation More ❯

learning, and probability theory. Ideally this would be within sports or gaming/betting industries. Understanding of techniques such as Monte Carlo simulation, Bayesian modelling, GLMs, mixed effects models, time series forecasting etc Strong programming ability, preferably in Python SQL and relational databases The company offer some great benefits including a bonus, subsidised office meals, gym membership More ❯

Experience with Python and SQL for data analysis, manipulation, and modeling. Basic understanding of machine learning: Familiarity with predictive modeling techniques and algorithms, in particular NLP, LLM's and Time Series Forecasting. Experience with data visualisation tools: Knowledge of tools like Tableau/Power BI, or similar to present data effectively. Strong analytical skills: Ability to interpret complex More ❯

Experience with Python and SQL for data analysis, manipulation, and modeling. Basic understanding of machine learning: Familiarity with predictive modeling techniques and algorithms, in particular NLP, LLM's and Time Series Forecasting. Experience with data visualisation tools: Knowledge of tools like Tableau/Power BI, or similar to present data effectively. Strong analytical skills: Ability to interpret complex More ❯

Machine Learning Engineer Solid knowledge of SQLandPython's ecosystem for data analysis (Jupyter, Pandas, Scikit Learn, Matplotlib). GCP, VertexAI experience is desirable (developing GCP machine learning services) Timeseries forecasting Solid understanding of computer science fundamentals, including data structures, algorithms, data modelling and software architecture Strong knowledge of Machine Learning algorithms (e.g. Logistic Regression, Random Forest, XGBoost, etc.) as … well as state-of-the-art research area (e.g. NLP, Transfer Learning etc.) and modern Deep Learning algorithms (e.g. BERT, LSTM, etc.) Machine Learning Engineer, timeseries, forecasting, VertexAI, GCP Reasonable Adjustments: Respect and equality are core values to us. We are proud of the diverse and inclusive community we have built, and we welcome applications from people of all More ❯