Data Applications Developer

Bradford
2 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineer

Senior Golang Developer - 2 Day London - Inside IR35

Data Scientist

GIS Technician

Frontend Developer/Design Lead

New Stack Developer

We are growing our IT team at pace and due to growth we are looking to hire a data applications developer.

Working in the Technology and Product development team you will joining a team of 4 currently, help build new and exciting cloud-based data and technology driven back-office products.

Client Details

We are a world leader in converged broadband, video and mobile communications and an active investor in cutting-edge infrastructure, content and technology ventures. With our investments in fibre-based and 5G networks we play a vital role in society, currently providing over 85 million fixed and mobile connections and rolling out the next generation of products and services, while readying our networks for 10 Gbps and beyond.

It is an exciting time to join us on our journey as we continue to grow our services; offering a wide range of opportunities and who embrace a culture of change and collaboration.

Description

The successful Data Applications Developer will be responsible for but not limited to:

  • Ability to be given business requirements and collaborate with the team to build solutions
  • Participate in product technical architecture design
  • Collaborate with the broader Technology and Product team to ensure the delivery and maintenance of exceptional service standards expected from our products and services
  • Maintain a close relationship with the group security team to ensure all our Products and Services are compliant

    Profile

    The successful Data Applications Developer will be able to demonstrate knowledge in most / all the following areas:

  • Demonstrable exposure with Python
  • Data engineering in the cloud, GCP
  • Background in building data applications in GCP
  • Comfortable working with solutions and products written in Python / SQL / Docker
  • Comfortable with Version Control Solutions such as GitHub and understand the basics of Branching, Merging and Pull Requests

    Desirable skills:

    Terraform / Bash
    Agile tools such as jira, confluenceJob Offer

    The successful Data Applications Developer will part of the Technology & Product team based in Bradford, we offer a hybrid working approach ( 2 days in the office. We actively encourage entrepreneurial thinking and you can quickly grow your career in our business. In addition to a great salary and a very competitive bonus we also offer:

    25 days holiday, with option to buy more.
    Private Medical insurance
    Dental insurance
    Critical Illness
    Personal accident insurance
    Pension Plan - Matched up to 10% And much more.

    Get in touch today for more information

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Jobs

Portfolio Projects That Get You Hired for Machine Learning Jobs (With Real GitHub Examples)

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!

Jobs Careers

Machine Learning Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.

Jobs

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.

🍪 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.