Senior Data Scientist
Immersum · London Area, United Kingdom
قدّم وتابع مع أبلاي إيدجSenior Data Scientist – Financial services / Data providerLocation: London / HybridSalary: £80-90k + 10% bonus + benefitsTech: Python, LLMs, Time Series Forecasting, ML, AI, AWS/Azure, SnowFlakeImmersum are supporting a well established technology-led business that is investing heavily in Data Science, AI and Machine Learning across its risk and trading functions. They're looking for a Senior Data Scientist who is genuinely hands-on and can take complex data problems from initial concept through to production deployment.The Role:This is a broad Data Science role covering predictive modelling, machine learning, time-series forecasting and modern AI/LLM applications. A particularly important part of the role is time-series forecasting. You must have genuine experience designing, building and deploying forecasting models from scratch and taking them into production.This isn't a role for someone who has simply consumed forecasting outputs or configured the forecasting functionality provided by AWS, GCP, Azure or another managed cloud service.You should have experience with the full modelling lifecycle — understanding the problem, exploring and preparing data, selecting and developing appropriate approaches, training and evaluating models, deploying them into production and subsequently monitoring and improving them. You'll also have the opportunity to work on LLM-powered applications, AI agents and multi-step AI workflows, moving beyond straightforward chatbot implementations.What we're looking for:3–5+ years experience in Data Science, Machine Learning, Econometrics or a related quantitative disciplineMSc or higher in Econometrics, Statistics, Mathematics, Physics or another quantitative subjectExpert-level PythonStrong experience with Pandas, NumPy, SciPy and Scikit-learnEssential: Proven hands-on experience designing, building and deploying time-series forecasting models from scratch into productionStrong understanding of time-series modelling and forecasting techniquesExperience working with commodity, financial or similarly complex time-series data would be highly beneficialProven experience taking models through the complete lifecycle: problem framing → data discovery → development → training → evaluation → deployment → monitoring → iterationHands-on experience with Machine Learning and LLMsExperience building AI applications beyond simple chatbot interfacesExperience developing production-grade PythonUnderstanding of modern ML production workflows, deployment and orchestrationFamiliarity with AWS, GCP, Snowflake or equivalent cloud technologiesExperience with frameworks such as LangChain, LangGraph or similar would be advantageousWhat you'll be doing:Design and build bespoke predictive and machine learning solutionsDevelop production-grade time-series forecasting models from first principlesTake forecasting models from experimentation through to real-world production deploymentBuild AI applications, agents and multi-step workflows using modern LLM technologiesWork closely with senior stakeholders to translate complex business problems into technical solutionsOwn projects end-to-end, rather than simply contributing to an individual stage of the processWork alongside Data Scientists, Analysts, Engineers and Product teamsMonitor, evaluate and continuously improve models once they're in productionMentor more junior members of the team and contribute to improving technical standardsIdentify practical applications for Machine Learning, Generative AI, LLMs and agentic workflowsThe key requirement:If you don't have hands-on experience designing and building your own time-series forecasting models and deploying them into production, this role won't be suitable. They're specifically looking for someone who understands the underlying modelling and statistical principles, rather than someone whose experience is primarily based around using pre-built forecasting models or managed forecasting services from cloud providers.If you're a Data Scientist with a strong time-series/forecasting background, excellent Python skills and a genuine interest in building production AI systems, I'd be keen to speak with you.