1 to 25 of 69 Time Series Analysis Jobs in England

applying their technical and quantitative skills to real-world investment opportunities and portfolio management. The Role You will play a key role in the analysis of new investment opportunities, working closely with experienced investment professionals across structured finance and mortgages. Key responsibilities will include: Cleansing, manipulating and summarising large … investment data sets and loan-level data tapes. Analysing loan-level time-series data to produce vintage and time-series analysis of defaults, recoveries, prepayments and other portfolio characteristics. Combining and aggregating data from multiple sources to identify patterns, correlations and trends. Deriving modelling assumptions ...

lead in resilient and growing categories. What sets us apart is our unique blend of deep human understanding and trusted science. Now it’s time to fully realise the full potential of our business and our people. We do this through our Win as One strategy. It puts … algorithms Deep understanding of Statistical/Probabilistic programming and Linear Algebra Be an expert in (Python, R, SQL) programming for Data Science and Time Series analysis Have in depth understanding of statistical modelling/ML techniques for time series forecasting (ARIMA, ETS, Prophet, Time ...

depth developed through industry experience is equally valued; expertise matters more than the credential Fluent in Python Strong experience with regression and classification, clustering, time-series analysis, anomaly detection, sequence-to-sequence architectures and stochastic optimisation Able to solve ambiguous problems independently and determine next steps without … building team capabilities. Highest-signal resume keywords Machine Learning Artificial Intelligence Python Programming Model Development Data Science Leadership ATS Optimization Keywords Hard Skills Regression Analysis Classification Clustering Time-Series Analysis Anomaly Detection Stochastic Optimisation Experiment Design Model Validation Model Deployment Monitoring Soft Skills Problem Solving Mentoring ...

data and AI/ML pipelines for advanced analytics and automated insight generation Apply machine learning, statistical modelling, deep learning, NLP, graph analytics and time-series analysis Prepare, transform and integrate large multi-source datasets, including sensor, geospatial and communications data Develop predictive models, prototypes and proof … multi-disciplinary agile teams with mission analysts and operational users Deliver intelligence data exploitation, advanced analytics, operational decision-support systems, data triage and automated analysis of large datasets Requirements Experience working in secure or highly regulated environments Understanding of handling sensitive or classified data Strong knowledge of modern data ...

evolve ambitious prototypes into a rock‐solid, scalable platform What you’ll actually do 50% Build — design & ship Agentic AI for CX: Real‐time assistants that listen to calls/chats, retrieve from customer KBs, and draft responses with human‐in‐the‐loop controls. Structured extraction: Schema‐driven pipelines … over unstructured text (and other modalities) using retrieval, tool‐use, and robust LLM prompting. Hybrid anomaly detection: Blend classical time‐series methods (e.g., decomposition, change‐point, forecasting) with LLM‐aware, contextful detectors for seasonality, spikes, step‐changes, and drift. Novelty discovery: Embedding‐based clustering and drift, topic surfacing ...

/AI to identify opportunities for influencing internal decision making as well as discussions on white papers/regulatory policy.You will perform hands-on analysis of integrated data from clinical trials and the real world to generate fit-for-purpose evidence that is applied to decision making in drug … business models, providing insight into structured and unstructured data.Apply R-based analytical and statistical techniques to solve business problemsApplying data cleaning, wrangling, and analysis techniques using tools like AI, R, Python and Pandas.Developing and managing data pipelines using tools like AI, R, Python, Bash, and SQL.Essential Requirements: Master ...

index arbitrage, and merger arbitrage strategies. The team is involved in research on topics including equity portfolio analytics, factor/factor model research, and analysis of best practices in the portfolio construction/investment process.The Senior Quantitative Researcher, PM Engagement, is responsible for working with equity PMs on their … their risk taking and improve their profitability and scalability. The researcher will be expected to contribute to the development of quantitative models for the analysis of portfolio risk & performance for strategies, including alternative equity strategies. Leveraging his or her excellent communications skills and deep understanding how investment process, portfolio ...

accessibility support we can offer, please click here. We’re a big business and we can offer a range of diverse full-time & part‐time working patterns across our many business areas, which meansthat we can find something that works for you. We work in a more blended … will: Design and improve deep learning and related machine learning forecasting models for large‐scale retailtime series. Build robust training and backtesting pipelines (time‐aware CV, leakage controls, stability checks). Apply best practices for productionisation (monitoring, retraining strategies, performance and cost considerations). Collaborate closely with engineering, product ...

Description SummaryThe mission of Novartis is to reimagine medicine, and our team advances that mission by applying advanced image analysis, computer vision, and AI methods to early drug discovery. We partner closely with experimental scientists, disease-area teams, data scientists, bioinformatics experts, and platform engineers to extract meaningful biological … organoids, tissue models).To grow this capability, we are seeking a seasoned, innovative, and collaborative data scientist with deep expertise in AI-enabled image analysis to join the Data Science team in Discovery Sciences (DSc) at Novartis Biomedical Research, Cambridge, MA. This role combines hands-on delivery of robust ...

value and potential of AI and advanced analytics through workshops, presentations and client engagements Applying modern data science techniques including statistical modelling, NLP, time-series analysis, spatial analysis and mathematical modelling Collaborating with multidisciplinary teams to deliver high-quality solutions in a fast-paced consulting environment ...

value and potential of AI and advanced analytics through workshops, presentations and client engagements Applying modern data science techniques including statistical modelling, NLP, time-series analysis, spatial analysis and mathematical modelling Collaborating with multidisciplinary teams to deliver high-quality solutions in a fast-paced consulting environment ...

development best practices (version control, testing, documentation).Experience with machine learning libraries such as scikit-learn, PyTorch, or Keras.Strong data visualization and exploratory data analysis skills.Ability to translate complex analytical concepts into clear, actionable insights.Strong collaboration and communication skills across multidisciplinary teams.Fluency in English (oral and written).This … disability benefits, a 401(k) with company contribution and match, and a variety of other benefits. In addition, employees are eligible for a generous time off package including vacation, personal days, holidays and other leaves.To learn more about the culture, rewards and benefits we offer our people click here.EEO ...

team. As a Lead Data Analyst, you’ll drive analytics within a dedicated customer operations model where we improve how we resolve complex and time‐sensitive customer issues—speed, reliability, quality, and end‐to‐end outcomes—and scale what works across our wider Operations teamsMost importantly, you’ll collaborate … stakes servicing interventions at scale.Predictive Modeling and Cause and Effect Analysis. Develop and implement robust models to predict outcomes and perform cause and effect analysis to identify key drivers, optimise processes, and enhance decision-making and strategic planning.Causal Inference and Quasi-Experimental Analysis. Develop robust approaches to cause ...

team. As a Lead Data Analyst, you'll drive analytics within a dedicated customer operations model where we improve how we resolve complex and time‐sensitive customer issues—speed, reliability, quality, and end‐to‐end outcomes—and scale what works across our wider Operations teamsMost importantly, you'll collaborate … servicing interventions at scale. Predictive Modeling and Cause and Effect Analysis. Develop and implement robust models to predict outcomes and perform cause and effect analysis to identify key drivers, optimise processes, and enhance decision-making and strategic planning. Causal Inference and Quasi-Experimental Analysis. Develop robust approaches to cause ...

statistical modelling, and machine learning with world-class engineering to build algorithms that optimise execution quality, minimise market impact, and adapt intelligently to real-time market conditions. Our work spans the full lifecycle of algorithmic trading — from research into price formation and liquidity dynamics, through model development and back … execution algorithms (e.g., VWAP, Participate, adaptive/liquidity‐seeking strategies) for cash equities. Conduct rigorous quantitative research on market microstructure, order‐book dynamics, venue analysis, and transaction cost analysis (TCA). Build and maintain statistical and machine learning models for short‐term price prediction, fill‐rate estimation, market ...

statistical modelling, and machine learning with world-class engineering to build algorithms that optimise execution quality, minimise market impact, and adapt intelligently to real-time market conditions.Our work spans the full lifecycle of algorithmic trading — from research into price formation and liquidity dynamics, through model development and back-testing … do.ResponsibilitiesEnhance execution algorithms (e.g., VWAP, Participate, adaptive/liquidity-seeking strategies) for cash equities.Conduct rigorous quantitative research on market microstructure, order-book dynamics, venue analysis, and transaction cost analysis (TCA).Build and maintain statistical and machine learning models for short-term price prediction, fill-rate estimation, market-impact ...

microstructure, statistical modelling, and machine learningwith world-class engineering to build algorithms that optimise execution quality, minimise market impact, and adapt intelligently to real-time market conditions. Our work spans the full lifecycle of algorithmic trading — from researchinto price formation and liquidity dynamics, throughmodel development and back-testing, toproduction … execution algorithms (e.g., VWAP, Participate, adaptive/liquidity-seeking strategies) for cash equities. Conduct rigorous quantitative research on market microstructure, order-book dynamics, venue analysis, and transaction cost analysis (TCA). Build and maintain statistical and machine learning models for short-term price prediction, fill-rate estimation, market ...

contributing to solution architecture, Preparing and presenting analytical results to business and technical stakeholders. Qualifications 6–8+ years of professional experience in data analysis, statistical modeling, computer vision or machine learning, including at least 4 years as a Data Scientist, Hands-on experience deploying ML models to production … English – both written and spoken (international client communication, presentations), Expertise in at least one of the following domains: Computer Vision, Large Language Models (LLMs), Time Series Analysis, Experience with TensorFlow, PyTorch, XGBoost, LightGBM, Proficiency with Git, Linux, Docker, MLflow, Airflow, AWS/GCP/Azure, Solid ...

delivers critical regulatory and risk metrics & analytics across risk domains (market, credit, liquidity, operational, capital) and firm activities via regular reporting, customized risk analysis, systematically generated risk reporting and risk tools. This role will focus on Market Risk. A&R has a unique viewpoint in the firm’s risk … team-oriented communication skills. Working knowledge of the financial industry, markets and products and associated non-financial risk. Working knowledge of mathematics including statistics, time series analysis and numerical algorithms. Experience with programming in Python and SQL for extract transform load (ETL) operations and data analysis ...

delivers critical regulatory and risk metrics & analytics across risk domains (market, credit, liquidity, operational, capital) and firm activities via regular reporting, customized risk analysis, systematically generated risk reporting and risk tools. This role will focus on Market Risk. A&R has a unique vista point in the firm … team-oriented communication skills. Working knowledge of the financial industry, markets and products and associated non-financial risk. Working knowledge of mathematics including statistics, time series analysis and numerical algorithms. Experience with programming in Python and SQL for extract transform load (ETL) operations and data analysis ...

delivers critical regulatory and risk metrics & analytics across risk domains (market, credit, liquidity, operational, capital) and firm activities via regular reporting, customized risk analysis, systematically generated risk reporting and risk tools. This role will focus on Market Risk.A&R has a unique vantage point in the firm’s risk … verbal and team-oriented communication skills.Working knowledge of the financial industry, markets and products and associated non-financial risk.Working knowledge of mathematics including statistics, time series analysis and numerical algorithms.Experience with programming in Python and SQL for extract transform load (ETL) operations and data analysis (including ...

delivers critical regulatory and risk metrics & analytics across risk domains (market, credit, liquidity, operational, capital) and firm activities via regular reporting, customized risk analysis, systematically generated risk reporting and risk tools. This role will focus on Market Risk.A&R has a unique vantage point in the firm’s risk … verbal and team-oriented communication skills.Working knowledge of the financial industry, markets and products and associated non-financial risk.Working knowledge of mathematics including statistics, time series analysis and numerical algorithms.Experience with programming in Python and SQL for extract transform load (ETL) operations and data analysis (including ...

Data Governance, Data Literacy, Data Quality, Data Science, Data Visualization, Graph Algorithms, Learning Agility, Machine Learning (ML), Machine Learning Algorithms, Python (Programming Language), Statistical Analysis, Time Series AnalysisSummaryLocation: Cambridge (USA)Type: Full time ...

modelling.Experience working with large datasets and performing detailed data analysis.Proficiency in one or more of Python, C#, C++ or Java.Experience within data science, quantitative analysis or statistical modelling.Strong analytical and problem-solving abilities.Excellent attention to detail and numerical accuracy.Strong communication skills and the ability to work effectively within … team.A proactive and inquisitive approach to solving complex problems.DesirableExperience developing predictive or statistical models.Knowledge of machine learning or advanced statistical techniques.Experience with time-series analysis, regression or optimisation.Experience working with real-time or high-volume datasets.A genuine interest in data-driven decision making and quantitative analysis.This ...

amounts of new satellite data and pioneering work in artificial intelligence, Vortexa creates an unprecedented view on the global seaborne energy flows in real-time, bringing transparency and efficiency to the energy markets and society as a whole.Ingesting data from multiple external vastly different sources at hundreds of rich … data points per second, moving terabytes of data while processing it in real time, running complex and complicated prediction and forecasting AI models while coupling their output into a hybrid human-machine data refinement process and presenting the result through a nimble low-latency SaaS solution used by customers ...