Graduate Data Scientist

Shift Technology
London
3 months ago
Applications closed

Related Jobs

View all jobs

Graduate Data Scientist - Client-Facing, Hybrid Edinburgh

Data Scientist

Data Scientist / Data Engineer within Defence & Security – Deloitte via AMS Skills Creation

Data Scientist

Data Scientist (Semantic Search/Recommender Systems)

Baseball Analyst / Data Scientist

Shift is the leading AI platform for insurance. Shift combines generative, agentic, and predictive AI to transform underwriting, claims, and fraud and risk — driving operational efficiency, exceptional customer experiences and measurable business impact. Trusted by the world\'s leading insurers, Shift delivers AI when and where it matters most, at scale and with proven results.

Our culture is built on innovation, trust, and a drive to transform the insurance industry through our SaaS platform. We come from more than 50 different countries and cultures and together we are creating the future of insurance.

As a Data Scientist you will work on a broad range of subjects actively contributing to the design and evolution of our suite of products focused on fraud detection, anti-money laundering, and claims automation. We are dedicated to providing innovative solutions, and you\'ll be part of a team with extensive technical and professional expertise in data science, data engineering, coding, business understanding, and client interactions. Additionally, we tackle a diverse array of data types, including structured data, unstructured text, documents, and images.

This opportunity is perfect for you if you\'re seeking a permanent role; Shift is the ideal place to kickstart your career journey!

You are a recent graduate, looking for your first full time Data Science opportunity.

What you\'ll do
  • You will actively participate in the development of our suite of products: fraud detection, anti-money laundering, and claim automation; and work on various data types such as structured data, free text, documents, and images.
  • Implementation of the data engineering, usually from client extracts to the insertion of the data in our data stores (SQL, ElasticSearch).
  • Developing, testing, tuning models, and putting them into production for tasks such as fraud detection and automation detection in complex environments.
  • Automate key business tasks by implementing them in our production process framework in C#
  • Conduct meetings with clients and interact with external stakeholders, whether it is for direct user feedback, presenting business cases, or defining the roadmap of evolutions.
What you bring

We are looking for candidates with diverse skills to help us build excellent technology solutions for our clients and be proficient in the following skills:

  • Code-savvy, either by having a degree in computer science and/or having developed some apps with actual users- writing scripts for models and notebooks is not enough at Shift, we thrive on people who can write maintainable, production-quality code that will run everyday without breaking.
  • AI-savvy, either by having a degree in machine learning and/or statistics. Having a clear understanding of statistics and machine learning problems, tasks and common resolutions is important to communicate internally and explain to the client how the product is working.
  • Client facing. You will need to be comfortable and open to communicating to our clients on a regular basis.
  • Business smart. We don\'t expect candidates to know the insurance sector, but we want applicants who are interested in learning and mastering the business aspects of our products.
  • Business fluent in English. We are an international company with offices in many countries and 40+ nationalities, the Shift working language is English.
  • Additional languages a Plus
Recruitment Process
  • Recruitment screening
  • Technical exercise
  • Technical interview with Senior Data Scientist
  • Final interview with Hiring Manager
Benefits
  • Flexible remote and hybrid working options
  • Competitive Salary and a variable component tied to personal and company performance
  • Company equity
  • Focus Fridays, a half-day each month to focus on learning and personal growth
  • Generous PTO and paid holidays
  • Mental health benefits
  • 2 MAD Days per year (Make A Difference Days for paid volunteering)

Additional benefits may be offered by country - ask your recruiter for more information. Intern and Apprentice position are eligible for some of these benefits - ask your recruiter for more details.

Shift is committed to providing reasonable accommodations for qualified individuals with disabilities in our application and employment process. If you require accommodation, please email and we will work with you to meet your accessibility needs.

Please be aware of scammers and only trust correspondence from emails ending in shift-technology.com. We will never initiate contact via Whatsapp/Text/SMS or ask for banking information or personal identification numbers as part of our recruitment process.

Shift does not accept unsolicited CVs from recruiters or employment agencies in response to the Shift Technology Careers page or a Shift Technology social media post. Any unsolicited CVs submitted are the property of Shift Technology.


#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.

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.

Data Science Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Thinking about switching into data science in your 30s, 40s or 50s? You’re far from alone. Across the UK, businesses are investing in data science talent to turn data into insight, support better decisions and unlock competitive advantage. But with all the hype about machine learning, Python, AI and data unicorns, it can be hard to separate real opportunities from noise. This article gives you a practical, UK-focused reality check on data science careers for mid-life career switchers — what roles really exist, what skills employers really hire for, how long retraining typically takes, what UK recruiters actually look for and how to craft a compelling career pivot story. Whether you come from finance, marketing, operations, research, project management or another field entirely, there are meaningful pathways into data science — and age itself is not the barrier many people fear.

How to Write a Data Science Job Ad That Attracts the Right People

Data science plays a critical role in how organisations across the UK make decisions, build products and gain competitive advantage. From forecasting and personalisation to risk modelling and experimentation, data scientists help translate data into insight and action. Yet many employers struggle to attract the right data science candidates. Job adverts often generate high volumes of applications, but few applicants have the mix of analytical skill, business understanding and communication ability the role actually requires. At the same time, experienced data scientists skip over adverts that feel vague, inflated or misaligned with real data science work. In most cases, the issue is not a lack of talent — it is the quality and clarity of the job advert. Data scientists are analytical, sceptical of hype and highly selective. A poorly written job ad signals unclear expectations and immature data practices. A well-written one signals credibility, focus and serious intent. This guide explains how to write a data science job ad that attracts the right people, improves applicant quality and positions your organisation as a strong data employer.