Data Scientist - Hybrid

TieTalent
Windsor
1 month ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist - Imaging - Remote - Outside IR35

Data Scientist - Measurement Specialist

Data Scientist (Predictive Modelling) – NHS

Data Scientist

Data Scientist

Overview

Join to apply for the Data Scientist - Hybrid role at TieTalent.

Responsibilities
  • Deliver high-quality data science and analytics solutions, contributing to design, development, and product roadmaps.
  • Collaborate with clients and internal teams to gather requirements, analyse data, and validate solutions.
  • Develop and implement descriptive, predictive, and prescriptive analytics, integrating data from multiple sources.
  • Produce clear documentation, reports, and visualisations.
  • Provide technical input for proposals, solution scoping, and proofs-of-concept.
  • Attend occasional client meetings or events across the UK, Europe, and internationally.
Required Experience
  • Strong knowledge of data modelling, machine learning, and/or advanced data analytics.
  • Demonstrable track record of delivering data analytics projects as part of a team.
  • Hands-on experience with collaborative software development and version control (preferably Git).
  • Familiarity with Agile/SCRUM methodologies.
  • Exposure to pre-engagement activities such as project scoping, technical feasibility analysis, or prototype development.
  • Comfortable contributing to technical discussions and implementing solutions defined by project leads.
Desirable Experience
  • Strong Python expertise.
  • Experience with GNU/Linux environments.
  • Familiarity with key data science and ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow, XGBoost, Hugging Face).
  • Experience in natural language processing, tabular data analysis, or computer vision.
  • SQL proficiency.
  • Exposure to containerisation (Docker, Kubernetes) and cloud-native architectures.
  • Experience with CI/CD, automated testing, and iterative product development.
  • Knowledge of graph databases and graph analysis.
Benefits
  • 35 days annual leave (including public holidays) plus up to 10 days unpaid leave.
  • Flexible working arrangements around core hours.
  • Private health insurance and pension scheme.
  • Contribution to gym membership.
  • Ongoing professional development support (courses, certifications, conferences).
  • Regular company outings, team celebrations, and knowledge-sharing sessions.
  • Monthly recognition of outstanding performance.
Additional Information

ALL APPLICANTS MUST BE FREE TO WORK IN THE UK.

Exposed Solutions is acting as an employment agency for this client. The advertisement does not discriminate and we welcome applications from any qualified persons.

Seniority level
  • Mid-Senior level
Employment type
  • Full-time
Job function
  • Engineering and Information Technology
Industries
  • Technology, Information and Internet


#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.

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

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

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

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.

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

Changing career into artificial intelligence in your 30s, 40s or 50s is no longer unusual in the UK. It is happening quietly every day across fintech, healthcare, retail, manufacturing, government & professional services. But it is also surrounded by hype, fear & misinformation. This article is a realistic, UK-specific guide for career switchers who want the truth about AI jobs: what roles genuinely exist, what skills employers actually hire for, how long retraining really takes & whether age is a barrier (spoiler: not in the way people think). If you are considering a move into AI but want facts rather than Silicon Valley fantasy, this is for you.