Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Data Scientist - Hybrid

TieTalent
Windsor
1 month ago
Create job alert
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

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

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.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.