Senior Simulation Engineer (Data Science)

Gousto
London
3 weeks ago
Create job alert

Job Description

Location: London, Hybrid 

We’re excited to be searching for a Senior Simulation Engineer (Internal title: Senior Data Scientist) to join Gousto and help shape the next phase of how we use data and simulation to drive smarter decisions across the business. At Gousto, data science is embedded across our teams, and this role offers the opportunity to work on complex, high-impact problems that directly influence efficiency, cost, and customer outcomes.

In this role, you’ll design and build simulation models and frameworks that enhance existing data science products and support continuous improvement across our operations. You’ll focus on building robust data pipelines, improving simulation capabilities over time, and enabling initiatives that deliver meaningful business value, without being tied to narrow, one-off analyses.

You’ll be part of a collaborative, cross-functional team, working closely with product managers, analysts and software engineers, and partnering with Data leadership to define OKRs, shape technical roadmaps and measure success against company goals. This is a fantastic opportunity for a senior data scientist who enjoys ownership, influence, and seeing their work make a real difference.

Core responsibilities

  • Design and build our end-to-end simulation capability, iterating over time to support new propositions and improve key business metrics.
  • Drive the continuous evolution of our experimental framework, developing tooling that strengthens and scales our simulation capability.
  • Stay close to the latest research and tooling in simulation, identifying practical opportunities to apply new ideas to real data science products.
  • Partner with a Senior Principal Data Scientist to identify broader opportunities for simulation technology, support data science product roadmaps, and help validate value and feasibility through discovery.
  • Work closely with software engineers to design and evolve the architecture for deploying simulation products, balancing performance, scalability and cost.
  • Identify and implement opportunities to reduce business-as-usual overhead for data science products, benefiting both the data team and wider stakeholders.
  • Own relationships with squad stakeholders, acting as the go-to expert for simulation-related questions and guidance.
  • Contribute to the wider data science community, sharing knowledge, promoting best practices, and helping build the data science brand internally and externally.
  • Play an active role in shaping the culture of the data science function and Gousto as a whole, contributing to initiatives beyond core OKR work such as inclusion, knowledge sharing and outreach.

Who you are

  • Strong knowledge of simulation technology, with experience applying it to real-world, production problems.
  • Confident working within the AWS ecosystem, including ECS tasks and Lambda functions, and comfortable with Docker, CloudFormation and CI/CD tooling such as CircleCI.
  • Highly proficient in Python, with strong experience using Java, SQL and PySpark in data-intensive environments.
  • Experienced in writing production-ready code and independently deploying and supporting data science products in live environments.
  • Comfortable working in cross-functional teams, partnering with analysts, software engineers and product managers to deliver end-to-end solutions.
  • Experienced in shaping and prioritising squad roadmaps, balancing technical excellence with business impact.
  • Able to manage multiple projects in parallel, adapting priorities as needs evolve.
  • Passionate about developing others, with experience mentoring junior data scientists.
  • Brings experience from operational domains such as supply chain, logistics or fulfilment.
  • Knowledge of optimisation techniques is a strong advantage, particularly where combined with simulation approaches.


Additional Information

Benefits

Click here to see our company benefits!

Gousto is for everyone

Whether it’s creating diversity in our recipes or building new teams, we care about our people and the opportunities they have at Gousto. Across our business we lead with inclusivity and strive for equality in all we do; working hard to ensure Gousto is an environment where you can be totally yourself.

Everyone is welcome and we’re looking for applications from people of all backgrounds and experiences. 

Excited but wondering if you tick every box? We recommend applying anyway so that we can review your profile . And, if you’re in a job share, why not just apply as a pair.

For our roles outside of Operations, most of our people spend 1 or 2 days in our offices every week, combining the benefits of flexibility and time together with colleagues. We want to enable you to do your best work, and if you require additional flexibility, please talk to us about it.

If you have a disability that you’re worried will affect you during the interview process, please let us know and we will do our best to help you feel comfortable.

We’d love it if you could submit your application online. If you require an alternative method of applying, please let us know. 

 

#LI-W1 

#LI-Hybrid

Related Jobs

View all jobs

Senior Data Scientist

Senior Machine Learning Engineer (Platform) - Bristol

Senior Machine Learning Engineer (Platform) - Exeter

Lead/Senior Data Scientist - Ad Tech Locational Data

Lead/Senior Data Scientist - Ad Tech Locational Data

Staff / VP, Data Scientist (UK)

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.