21 of 21 Permanent 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 ❯

of passionate engineers and industry experts, applying data engineering and data science techniques to optimize supply chain processes. Your expertise will directly contribute to providing our clients with real-time visibility, predictive analytics, and actionable insights. What You Will Do Develop and implement machine learning models to improve the accuracy of supply chain ETA s. Analyze large, complex datasets … such as regression analysis, neural networks, or ensemble methods can predict ETAs more accurately by considering various factors like traffic conditions, weather, route efficiency, and historical performance. 2. Real-Time Data Integration: Incorporate real-time data into predictive models. This includes traffic updates, weather conditions, vehicle speed, and location data. Real-time data allows for dynamic adjustments … help in adjusting the predictive models to account for recurrent issues. 4. Route Optimization: Use data analytics to identify the most efficient routes. Optimized routing not only shortens travel time but also makes ETA predictions more reliable. 5. Machine Learning for Anomaly Detection: Implement machine learning algorithms to detect anomalies that could affect delivery times, such as unexpected traffic 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 ❯

role in shaping smarter pricing, deal governance, and business performance through cutting-edge machine learning. In this hands-on role, you’ll develop models that drive pricing optimisation, margin forecasting, and deal scoring. Turning data into actionable insights for high-stakes commercial decisions. From regression and clustering to time series forecasting, you’ll apply advanced techniques More ❯

role in shaping smarter pricing, deal governance, and business performance through cutting-edge machine learning. In this hands-on role, you’ll develop models that drive pricing optimisation, margin forecasting, and deal scoring. Turning data into actionable insights for high-stakes commercial decisions. From regression and clustering to time series forecasting, you’ll apply advanced techniques 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: Utilize econometric techniques like regression analysis, time series modeling, 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 … machine learning to enhance model accuracy and uncover deeper insights. Required Skills: Strong Econometrics Background: Expertise in statistical methods like linear regression, generalized linear models, panel data analysis, and time series forecasting. Data Science Proficiency: Proficient in programming languages like Python, R, and SQL including data manipulation, data imputation, statistical modeling, and visualization libraries. Media Industry Knowledge: Understanding 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 ❯

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 ❯

model interpretability, graph neural nets, among others. We are looking for a Machine Learning Scientist with a strong academic background in the areas of machine learning, natural language processing, 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 … way possible, this is your chance to make history. About the team 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 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 ❯

Location: London (hybrid working 3 office days per week) Employment Type: Permanent, full time Think the AA is just about roadside assistance? Think again. For over a century, we've been evolving and adapting. Today, as the nation's leading motoring organisation, we offer a wide range of products and services to millions of customers. From roadside assistance to … do I need? Experienced in digital analytics, with strong stakeholder engagement skills. Proficiency in SQL, with experience in advanced query techniques. Experience using data science techniques (regression analysis and time series forecasting) is highly desirable. Hands-on experience with web and app analytics tools (GA4 preferred, Adobe also valuable). Strong data storytelling skills, with the ability 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 ❯