Data Science Placement Programme

Comptia Data+
Maidstone
5 days ago
Applications closed

Related Jobs

View all jobs

Data Science Placement Programme

Data Science Placement Programme

Data Science Placement Programme

Data Science Placement Programme

Data Science Placement Programme

Data Science Placement Programme

Overview

We are recruiting for companies who are looking to employ our Data Science Traineeship graduates to keep up with their growth. The best part is you will not need any previous experience as full training will be provided. You will also have the reassurance of a job guarantee within 20 miles of your location upon completion.

Whether you are working full time, part-time or unemployed, this package has the flexibility to be completed at a pace that suits you.

Program Structure
  1. Step 1 - Full Data Science Career Training

    You will begin your data science journey by studying a selection of industry-recognized courses that will take you from beginner level all the way through to being qualified to work in a junior Data Scientist role. Through the interactive courses, you will gain knowledge in Python, R, Machine Learning, AI, and much more. You will also complete mini projects to gain practical experience and test your skills while you study. This step will fully prepare you for the professional projects that you will undertake in step 4 of this process. At the end of this step, you will complete a short online multiple-choice exam to showcase your understanding of the courses before moving on to step 2.

  2. Step 2 - CompTIA Data+
  3. Step 3 - Official Exam

    The CompTIA Data+ exam will certify that you have knowledge and skills required to transform business requirements in support of data-driven decisions through mining and manipulating data, applying basic statistical methods, and analysing complex datasets while adhering to governance and quality standards. The exam is 90 minutes long and can be sat either in your local testing centre or online.

  4. Step 4 - Practical Projects

    Now that you have completed your theory training and official exams, you will be assigned 2 practical projects by your tutor. The projects are the most important part of the traineeship as it will showcase to employers that you have skills required to work in a data science role. The projects will use real world scenarios where you be utilising all of the skill that you have learned. While you are progressing through the projects, you will have the ongoing support from your personal tutor. Once both projects have been completed and given the final sign off, you will have completed the traineeship and will be ready to move onto the recruitment stage.

Your Data Science Role

Once you have completed all of the mandatory training, which includes the online courses, practical projects and building your own portfolio, we will place you into a Data Scientist role, where you will be guaranteed a great starting salary. We have partnered with a number of large organisations strategically located throughout the UK, providing a nationwide reach of jobs for our candidates.

At a one off cost of £1495, or a deposit of £212 followed by 10 interest free monthly instalments of £148, this represents a great opportunity to start a rewarding career in IT and have a real career ladder to start climbing. If you are not offered a role at the end of the training we will refund 100% of your course fees.


#J-18808-Ljbffr

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.

Careers

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

Jobs

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

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

Education

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

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.