Location: London / Hybrid
Immersum 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 discipline
- MSc or higher in Econometrics, Statistics, Mathematics, Physics or another quantitative subject
- Expert-level Python
- Strong experience with Pandas, NumPy, SciPy and Scikit-learn
- Essential: Proven hands-on experience designing, building and deploying time-series forecasting models from scratch into production
- Strong understanding of time-series modelling and forecasting techniques
- Experience working with commodity, financial or similarly complex time-series data would be highly beneficial
- Hands-on experience with Machine Learning and LLMs
- Experience building AI applications beyond simple chatbot interfaces
- Understanding of modern ML production workflows, deployment and orchestration
- Familiarity with AWS, GCP, Snowflake or equivalent cloud technologies
- Experience with frameworks such as LangChain, LangGraph or similar would be advantageous
What you’ll be doing:
- Design and build bespoke predictive and machine learning solutions
- Develop production-grade time-series forecasting models from first principles
- Take forecasting models from experimentation through to real-world production deployment
- Build AI applications, agents and multi-step workflows using modern LLM technologies
- Work closely with senior stakeholders to translate complex business problems into technical solutions
- Own projects end-to-end, rather than simply contributing to an individual stage of the process
- Work alongside Data Scientists, Analysts, Engineers and Product teams
- Monitor, evaluate and continuously improve models once they’re in production
- Mentor more junior members of the team and contribute to improving technical standards
- Identify practical applications for Machine Learning, Generative AI, LLMs and agentic workflows
The 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.
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