Junior Data Scientist - AI Practice Team

American Bureau of Shipping
Warrington
3 weeks ago
Create job alert

ABS is seeking an exceptional Junior Data Scientist to join us full-time on our Artificial Intelligence (AI) Practice Team, Europe. In this role, you will support AI consulting engagements focused on policy, data, and document-centric solutions by preparing, analyzing, and modeling client data as part of a multidisciplinary delivery team. Working closely with senior data scientists, consultants, and domain experts, you will help turn real-world datasets into actionable insights, features, and reusable assets that underpin our AI solutions. Based in Warrington or London, England with some remote flexibility, you will gain exposure to modern AI, data tooling, and industrial use cases while building robust, production-aware analytics skills.

What You Will Do:

Support AI consulting engagements by cleaning, structuring, and analyzing client data (tabular, time-series, and document-based) to enable modeling and insight generation. Contribute to development, testing, and documentation of machine learning models, analytics pipelines, and proof-of-concept solutions under guidance from senior data scientists. Work with our document and data services to extract, transform, and enrich information from reports, PDFs, logs, and other unstructured sources using NLP and related techniques. Build and maintain basic dashboards, reports, and visualizations (, in Python, Power BI, or similar tools) to communicate findings to consultants and client stakeholders. Collaborate with consultants and domain experts to translate business questions into analytical tasks, validate results, and refine approaches based on feedback. Help maintain clean, reproducible project assets (code, notebooks, datasets, documentation) using modern collaboration and version control tools.

What You Will Need:

Education and Experience

Bachelor’s degree in a STEM discipline (, Data Science, Computer Science, Engineering, Mathematics, Statistics) or related field, or equivalent practical experience. + years of combined experience through projects, internships, or professional roles applying data science/ML methods and tools. Practical experience applying core techniques in data preprocessing, modeling, and evaluation using Python, SQL, and common ML libraries. Exposure to AI/ML or analytics projects in academic, research, or professional environments, ideally with real-world or messy datasets. Familiarity with cloud-based and modern data platforms (, Azure, AWS, GCP, Databricks) and BI tools is a plus but not mandatory.

Knowledge, Skills, and Abilities

Strong foundation in data science/ML concepts and statistics, with hands-on experience in Python (, pandas, scikit-learn) and working with SQL-based data sources. Ability to clean, structure, and analyze real-world datasets, including unstructured or semi-structured data (, documents, logs, text). Comfortable working with Jupyter notebooks and Git-based workflows for reproducible and version-controlled analysis. Clear, structured communication skills, including the ability to explain analytical work and findings to non-technical stakeholders in a concise, business-relevant way. Collaborative mindset and willingness to learn, taking feedback from senior team members and adapting quickly to new tools, methods, and domains. Organized, detail-oriented working style, with the ability to manage tasks across multiple projects and meet deadlines reliably. Must hold a valid right to work status in the UK.

Nice to Have

Experience applying ML/NLP to real datasets (, classification, forecasting, document information extraction, OCR, LLMs, or search/retrieval systems). Exposure to cloud platforms (Azure/AWS/GCP), ML tooling (, Databricks, MLflow, Docker), and BI/visualization tools (Power BI, Tableau). Any exposure to industrial, maritime, or asset-intensive domains, or to consulting/client-facing environments. 

Reporting Relationships:

Thiis role reports to the Senior Data Scientist and does not include direct reports.

Related Jobs

View all jobs

Junior Data Scientist

Junior Data Scientist

Junior Data Scientist

Junior Data Scientist

Junior Data Scientist: Drive Advertising & Creative Optimization

Junior Data Scientist – Remote Pricing & ML

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.