20 of 20 Time Series Analysis Jobs in London

Lead — AI Agents, Structured Insights & Detection Location: London, hybrid About Anecdote Anecdote we’re on a mission to make customer experience delightful for everyone involved . Think a real‐time copilot that listens to live calls and chats, reads our customers’ knowledge bases, and drafts high‐quality replies for human agents - while also turning messy, multi‐channel feedback into … leads, directors, and the CTO to 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, LLM summarization of emerging themes with deduplication and evidence links. Alerting & scoring: Severity/ More ❯

Lead — AI Agents, Structured Insights & Detection Location: London, hybrid About Anecdote Anecdote we’re on a mission to make customer experience delightful for everyone involved . Think a real‐time copilot that listens to live calls and chats, reads our customers’ knowledge bases, and drafts high‐quality replies for human agents - while also turning messy, multi‐channel feedback into … leads, directors, and the CTO to 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, LLM summarization of emerging themes with deduplication and evidence links. Alerting & scoring: Severity/ More ❯

Lead — AI Agents, Structured Insights & Detection Location: London, hybrid About Anecdote Anecdote we’re on a mission to make customer experience delightful for everyone involved . Think a real‐time copilot that listens to live calls and chats, reads our customers’ knowledge bases, and drafts high‐quality replies for human agents - while also turning messy, multi‐channel feedback into … leads, directors, and the CTO to 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, LLM summarization of emerging themes with deduplication and evidence links. Alerting & scoring: Severity/ More ❯

Lead — AI Agents, Structured Insights & Detection Location: London, hybrid About Anecdote Anecdote we’re on a mission to make customer experience delightful for everyone involved . Think a real‐time copilot that listens to live calls and chats, reads our customers’ knowledge bases, and drafts high‐quality replies for human agents - while also turning messy, multi‐channel feedback into … leads, directors, and the CTO to 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, LLM summarization of emerging themes with deduplication and evidence links. Alerting & scoring: Severity/ More ❯

Overview Department: Technology Employment Type: Permanent - Full Time Location: UK - London Reporting To: Beth Rice Compensation: £110,000 - £130,000/year At Field, we have spent the last few years developing our automated energy trading platform, Gaia. We deployed Gaia to trade in real-time for our first physical asset in GB in early November 2024. We … are improving our algorithms all the time, and over the coming years we will be deploying Gaia on more GB assets as well as assets across Europe (Germany, Italy and Spain). You will be part of a small, fast moving team of certified power traders, wearing multiple hats, and you will have a tangible impact shaping how we … be one of the key responders for any aspect of trading that requires humans in the loop, such as responding to unplanned or emergency scenarios. This is an exciting time to join Field, right at the core of the business. In the next few years our team's responsibility will expand rapidly as we improve Gaia and deploy it More ❯

solving skills. You are someone who knows the fundamentals of machine learning and/or operations research and knows when they should be applied, and ideally have experience with time series analysis or forecasting. You are a keen problem solver, able to think deeply about a business problem and devise a well-thought-out and pragmatic algorithmic … insights are aligned with the direction the business is heading in. You should also be proactive in gathering input from relevant stakeholders to enhance the accuracy and relevance of analysis you produce Ability to take a fuzzy business objective and turn it into a problem that can be solved via machine learning and optimisation Comfortable working in a fast … and we prioritise their welfare. Benefits differ by country, but we offer many benefits in areas including healthcare, well-being, parental leave, pensions, and generous annual leave allowances, including time off to support a charitable cause of your choice. Benefits are country-specific, please ask your recruiter for more information. Diversity At Deliveroo, we believe a great workplace is More ❯

trading at a hedge fund, proprietary trading firm, or top-tier investment bank Proven track record of alpha generation or contribution to profitable strategies Deep understanding of statistical modeling, time-series analysis, and/or machine learning techniques Strong programming skills in Python, C++, or similar; experience working with large datasets and research infrastructure Master’s or More ❯

trading at a hedge fund, proprietary trading firm, or top-tier investment bank Proven track record of alpha generation or contribution to profitable strategies Deep understanding of statistical modeling, time-series analysis, and/or machine learning techniques Strong programming skills in Python, C++, or similar; experience working with large datasets and research infrastructure Master’s or More ❯

trading at a hedge fund, proprietary trading firm, or top-tier investment bank Proven track record of alpha generation or contribution to profitable strategies Deep understanding of statistical modeling, time-series analysis, and/or machine learning techniques Strong programming skills in Python, C++, or similar; experience working with large datasets and research infrastructure Master’s or More ❯

trading at a hedge fund, proprietary trading firm, or top-tier investment bank Proven track record of alpha generation or contribution to profitable strategies Deep understanding of statistical modeling, time-series analysis, and/or machine learning techniques Strong programming skills in Python, C++, or similar; experience working with large datasets and research infrastructure Master’s or More ❯

Strong STEM background (PhD/Masters ideal) ✔️ 3+ years in execution research/TCA/market-impact modelling ✔️ Python expertise (C Rust a bonus) ✔️ Deep stats/ML knowledge & time-series analysis 👉 A chance to work with some of the sharpest minds in trading & tech, in a high-performance environment where ideas move fast. Please get in More ❯

Strong STEM background (PhD/Masters ideal) ✔️ 3+ years in execution research/TCA/market-impact modelling ✔️ Python expertise (C Rust a bonus) ✔️ Deep stats/ML knowledge & time-series analysis 👉 A chance to work with some of the sharpest minds in trading & tech, in a high-performance environment where ideas move fast. Please get in More ❯

Strong STEM background (PhD/Masters ideal) ✔️ 3+ years in execution research/TCA/market-impact modelling ✔️ Python expertise (C Rust a bonus) ✔️ Deep stats/ML knowledge & time-series analysis 👉 A chance to work with some of the sharpest minds in trading & tech, in a high-performance environment where ideas move fast. Please get in More ❯

Strong STEM background (PhD/Masters ideal) ✔️ 3+ years in execution research/TCA/market-impact modelling ✔️ Python expertise (C Rust a bonus) ✔️ Deep stats/ML knowledge & time-series analysis 👉 A chance to work with some of the sharpest minds in trading & tech, in a high-performance environment where ideas move fast. Please get in More ❯

basis. You will be responsible for designing, developing, and deploying deep learning models to solve complex real-world problems across domains such as computer vision, natural language processing, and time-series analysis. Key Responsibilities: Design and implement deep learning models using frameworks such as PyTorch or TensorFlow. Collaborate with data scientists, ML engineers, and product teams to define More ❯

basis. You will be responsible for designing, developing, and deploying deep learning models to solve complex real-world problems across domains such as computer vision, natural language processing, and time-series analysis. Key Responsibilities: Design and implement deep learning models using frameworks such as PyTorch or TensorFlow. Collaborate with data scientists, ML engineers, and product teams to define More ❯

basis. You will be responsible for designing, developing, and deploying deep learning models to solve complex real-world problems across domains such as computer vision, natural language processing, and time-series analysis. Key Responsibilities: Design and implement deep learning models using frameworks such as PyTorch or TensorFlow. Collaborate with data scientists, ML engineers, and product teams to define More ❯

basis. You will be responsible for designing, developing, and deploying deep learning models to solve complex real-world problems across domains such as computer vision, natural language processing, and time-series analysis. Key Responsibilities: Design and implement deep learning models using frameworks such as PyTorch or TensorFlow. Collaborate with data scientists, ML engineers, and product teams to define More ❯

non-technical stakeholders. Technical Prowess: You have a strong command of quantitative trading principles and are proficient with relevant technologies. Deep knowledge of statistical modelling, machine learning techniques, and time series analysis. Hands-on experience with back-testing frameworks and simulation environments. A strong understanding of various market data APIs, trading protocols (e.g., FIX), and exchange connectivity. Qualifications More ❯

non-technical stakeholders. Technical Prowess: You have a strong command of quantitative trading principles and are proficient with relevant technologies. Deep knowledge of statistical modelling, machine learning techniques, and time series analysis. Hands-on experience with back-testing frameworks and simulation environments. A strong understanding of various market data APIs, trading protocols (e.g., FIX), and exchange connectivity. Qualifications More ❯