Mid-Level Data Scientists Needed |Financial Services | Guildford Area

Guildford
10 months ago
Applications closed

Related Jobs

View all jobs

Electrical & Control Engineer

Earthworks Engineer

Maintenance Engineer

Trainee AI Engineer Placement Programme

Senior Controls Engineer

Maintenance Engineer

Mid-Level Data Scientists Needed |Financial Services | Guildford Area

Are you a passionate data scientist with a knack for engineering solutions? Our established financial services client is seeking a talented Mid-Level Data Scientist to join their growing Analytics team at their office near Guildford.

About the Role:

Working in a Data Science role you will also perform some Data Engineering and Analysis tasks. You'll help transform complex financial data into actionable insights that drive business decisions. You'll collaborate with cross-functional teams to develop predictive models using a range of Data Science techniques. They are also planning to implement some Generative AI tools that optimize internal operations. They are still early in their Data Science journey and this will be area they are investing over the next few years so need people who can help shame their Data and AI tools.

Responsibilities:

  • Design, develop and implement predictive models and machine learning algorithms including building Gen-AI tools.

  • Build and maintain data pipelines to support analytical workflows

  • Transform raw financial data into structured formats suitable for analysis

  • Create visualizations and reports to communicate findings to stakeholders

  • Collaborate with business teams to understand requirements and deliver solutions

  • Optimize existing models and processes for improved performance

    Requirements:

  • 3+ years of experience in data science using a range of predictive modelling and Machine Learning techniques

  • Strong programming skills in Python and SQL

  • Experience with data engineering concepts and tools (ETL pipelines, data warehousing – they are using SnowFlake)

  • Knowledge of machine learning libraries and frameworks (e.g., scikit-learn, TensorFlow)

  • Bachelor's degree in Computer Science, Statistics, Mathematics, or related field

    Technical Skills:

  • Data manipulation: Pandas, NumPy

  • Data engineering: Snowflake, Apache Spark, Airflow or similar

  • Database management: SQL, NoSQL databases

  • Visualization: Power BI, Tableau, or equivalent

  • Version control: Git

    Salary: £45,000 - £65,000 DOE + good pension contribution + private medical + 25 days holiday + discretionary bonus

    Join their team and help shape business success through data-driven decision making.

    Location: Guildford area, Surrey Work Model: Hybrid (3 days in office, 2 days remote)

    APPLY TODAY for immediate consideration and interview in the next week

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 Robotics Tools Do You Need to Know to Get a Robotics Job?

If you’re pursuing a career in robotics, it can feel like the list of tools you should learn never ends. One job advert asks for ROS, another mentions Gazebo, another wants experience with Python, Linux, C++, RobotStudio, MATLAB/Simulink, perception stacks, control frameworks, real-time OS, vision libraries — and that’s just scratching the surface. With so many frameworks, languages and platforms, it’s no wonder robotics job seekers feel overwhelmed. But here’s the honest truth most recruiters won’t say explicitly: 👉 They don’t hire you because you know every tool — they hire you because you can apply the right tools to solve real robotics problems reliably and explain your reasoning clearly. Tools matter — but only in service of outcomes. So the real question isn’t how many tools you should know, but which tools you should master and why. For most robotics roles, the answer is significantly fewer — and far more focused — than you might assume. This article breaks down what employers really expect, which tools are core, which are role-specific, and how to focus your learning so you look capable, confident, and ready to contribute from day one.

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

Robotics is one of the most dynamic, interdisciplinary fields in technology — blending mechanical systems, embedded software, controls, perception (AI/vision), modelling, simulation and systems integration. Hiring managers in this space are highly selective because robotics teams need people who can solve real-world problems under constraints, work across disciplines, and deliver safe, reliable systems. And here’s the reality: hiring managers do not read every word of your CV. Like in many tech domains, they scan quickly — often forming a judgement in the first 10–20 seconds. In robotics, those first signals are especially important because the work is complex and there’s a wide range of candidate backgrounds. This guide unpacks exactly what hiring managers look for first in robotics applications and how to optimise your CV, portfolio and cover letter so you stand out in the UK market.

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

Robotics is no longer confined to science fiction or isolated research labs. Today, robots perform critical tasks across manufacturing, healthcare, logistics, agriculture, defence, hospitality and even education. In the UK, businesses are embracing automation to improve productivity, reduce costs and tackle labour shortages. Yet despite strong interest and a growing number of university programmes in robotics, many employers report a persistent problem: graduates are not job-ready for real-world robotics roles. This is not a question of intelligence or dedication. It is a widening skills gap between what universities teach and what employers actually need in robotics jobs. In this article, we’ll explore that gap in depth — what universities do well, where their programmes often fall short, why the disconnect exists, what employers really want, and how you can bridge the divide to build a thriving career in robotics.