Senior Data Scientist

Senior Data Scientist

Full-Time 63000 - 77000 £ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Design and build innovative predictive models and AI applications from scratch.
  • Company: Leading tech firm investing in Data Science and AI for risk and trading.
  • Benefits: Hybrid work, competitive salary, and opportunities for professional growth.
  • Other info: Collaborative environment with mentorship opportunities and career advancement.
  • Why this job: Make a real impact by solving complex data problems with cutting-edge technology.
  • Qualifications: 3-5+ years in Data Science, strong Python skills, and hands-on forecasting experience.

The predicted salary is between 63000 - 77000 £ per year.

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.

Senior Data Scientist employer: Immersum

As a Senior Software Engineer at our innovative company, you will thrive in a dynamic remote work environment that champions collaboration and creativity. We offer competitive salaries, comprehensive benefits, and ample opportunities for professional growth, ensuring you can develop your skills while making a meaningful impact in the AI space. Join us to be part of a forward-thinking team that values your contributions and fosters a culture of mentorship and excellence.

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Contact Details:

Immersum Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Senior Data Scientist

Get Involved in Data Science Meetups

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Show Off Your Projects

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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Immersum.

Apply Directly through Our Website

When you find a suitable opening like Senior Data Scientist at Immersum, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Senior Data Scientist

Data Science
Machine Learning
Time-Series Forecasting
Predictive Modelling
Python
Pandas
NumPy

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at Immersum, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Immersum. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at Immersum

Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Immersum!

Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.