Data Scientist

Technical Staffing Resources
Warrington
11 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist - Production

Data Scientist/Machine Learning Engineer - RNA Design

Data Scientist - active NPPV3 required

Technical Staffing Resources (TSR) are the in-house agency and master vendor for KBR who are a leading global engineering, construction, and services company.

KBR support the hydrocarbon and government services markets on six continents. Serving their customers through diverse business units, KBR offer challenging assignments on some of the world's largest and most complex projects.

KBR are looking to recruit a Data Scientist on a 12 month contract based in Warrington / Cumbria

On Offer:

Competitive hourly pay rate Outside IR35, highly likely so engagement through a LLC is permitted Hybrid working - 3 days in the office, 2 days from home

Role Overview
The role is part of the PPP support to the Digital Asset Management (DAM) programme within Sellafield. The PPP support to DAM is an integrated project team with members from PPP and Sellafield’s asset management capability.

The DAM programme is a site wide delivery improvement programme supporting Sellafield’s improvement requirements, the programme aims to address a number of issues with Sellafield’s asset management arrangements with a targeted outcome of: “An integrated information line of sight from the asset through to the enterprise that integrates activities across the asset lifecycle, removes the burden of paper-based work processes from our teams and engages everyone in the use of modern digital technologies to inform decision making”

Responsibilities
• Development with Microsoft Visual Studio IDE and browser versions 
• Developing solutions within agile delivery projects. 
• Sprint backlog ratification.
• Data mapping of API interfaces as an enterprise
• Rapid prototyping and deployment.
• Design and delivery of security accredited solutions.

• Experience in:REST API development using an Enterprise Integration Hub likely to be Azure Integration Services using C# and ISS Web Servers
• REST API modelling including Swagger
• C#
• Rest API management and monitoring
• Python 
• Delivery with agile methods, such as SCRUM 
• At least three years’ experience as a data scientist of solutions within a secure environment
• Experience in use of industry standard methods for documenting and controlling the configuration of code.
• Proven ability to collaborate with team members and a wide range of people.
• Demonstrates good organisational skills giving the ability to deliver to timeframes and estimates.
• Demonstrates good written, oral, comprehension and presentational skills. 

Skills / ESSENTIAL
• Proven ability with JSON, YAML, REST, python 
• Ability to think creatively and code “on-the -fly” when supporting client experimentation.
• Proven experience in the delivery of software development.
• Experience in the design and review of software development.
• Knowledge of both traditional and DevSecOps approaches to software implementation.
• Knowledge of the tools and processes for DevSecOps continuous build and integration related to data storage and presentation tools.
• Hold, have held, or eligible to apply for UK based security clearance – SC or better.
• Recognised certification e.g., Microsoft.

Skills / DESIRABLE
• Knowledge and experience of:
• Exposure to complex data environments.
• Information security constraints and best practice.
• Implementation of common data models and data migration required.
• Knowledge of market leading Data manipulation and presentation tools.

NB - To be considered for this position you must have the right to live and work in the UK. be able to complete BPSS Security Clearance.

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 AI Jobs (With Real GitHub Examples)

In the fast-evolving world of artificial intelligence (AI), an impressive portfolio of projects can act as your passport to landing a sought-after role. Even if you’ve aced interviews in the past, employers in AI and machine learning (ML) are increasingly asking candidates to demonstrate hands-on experience through the projects they’ve built and shared online. This is because practical ability often speaks volumes about your suitability for a role—far more than any exam or certification alone could. In this article, we’ll explore how to build an outstanding AI portfolio that catches the eye of recruiters and hiring managers, including: Why an AI portfolio is crucial for job seekers. How to choose AI projects that align with your target roles. Specific project ideas and real GitHub examples to help you stand out. Best practices for showcasing your work, from writing clear READMEs to using Jupyter notebooks effectively. Tips on structuring your GitHub so that employers can instantly see your value. Moreover, we’ll discuss how you can use your portfolio to connect with top employers in AI, with a handy link to our CV-upload page on Artificial Intelligence Jobs for when you’re ready to apply. By the end, you’ll have a clear roadmap to building a portfolio that will help secure interviews—and the AI job—of your dreams.

Jobs Careers

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

In today's competitive AI job market, nailing a technical interview can be the difference between landing your dream role and getting lost in the crowd. Whether you're looking to break into machine learning, deep learning, NLP (Natural Language Processing), or data science, your problem-solving skills and system design expertise are certain to be put to the test. AI‑related job interviews typically involve a range of coding challenges, algorithmic puzzles, and system design questions. You’ll often be asked to delve into the principles of machine learning pipelines, discuss how to optimise large-scale systems, and demonstrate your coding proficiency in languages like Python, C++, or Java. Adequate preparation not only boosts your confidence but also reduces the likelihood of fumbling through unfamiliar territory. If you’re actively seeking positions at major tech companies or innovative AI start-ups, then check out www.artificialintelligencejobs.co.uk for some of the latest vacancies in the UK. Meanwhile, this blog post will guide you through 30 real coding & system-design questions you’re likely to encounter during your AI job interview. This list is designed to help you practise, anticipate typical question patterns, and stay ahead of the competition. By reading through each question and thinking about the possible approaches, you’ll sharpen your problem-solving skills, time management, and critical thinking. Each question covers fundamental concepts that employers regularly test, ensuring you’re well-equipped for success. Let’s dive right in.

Jobs

Negotiating Your AI Job Offer: Equity, Bonuses & Perks Explained

Artificial intelligence (AI) has proven itself to be one of the most transformative forces in today’s business world. From smart chatbots in customer service to predictive analytics in finance, AI technologies are reshaping how organisations operate and innovate. As the demand for AI professionals grows, so does the complexity of compensation packages. If you’re a mid‑senior AI professional, you’ve likely seen job offers that include far more than just a base salary—think equity, bonuses, and a range of perks designed to entice you into joining or staying with a company. For many, the focus remains squarely on salary. While that’s understandable—after all, your monthly take‑home pay is what covers day-to-day expenses—limiting your negotiations to salary alone can leave considerable value on the table. From stock options in ambitious startups to sign‑on bonuses that ‘buy you out’ of your current contract, modern AI job offers often include elements that can significantly boost your long-term wealth and job satisfaction. This article aims to shed light on the full scope of AI compensation—specifically focusing on how equity, bonuses, and perks can enhance (or sometimes detract from) the overall value of your package. We’ll delve into how these elements work in practice, what to watch out for, and how to navigate the negotiation process effectively. Our goal is to provide mid‑senior AI professionals with the insights and tools to land a holistic compensation deal that accurately reflects their technical expertise, leadership potential, and strategic importance in this fast-moving field. Whether you’re eyeing a leadership role in machine learning at an established tech giant, or you’re considering a pioneering position at a disruptive AI startup, the knowledge in this guide will help you weigh the merits of base salary alongside the potential riches—and risks—of equity, bonuses, and other benefits. By the end, you’ll have a clearer sense of how to align your compensation with both your immediate lifestyle needs and long-term career aspirations.

🍪 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.