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Junior Data Scientist - AI Practice Team
American Bureau of Shipping (ABS) —Warrington
- Full-time
- Azure
- SQL
- AWS

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Junior Data Scientist - AI Practice Team

American Bureau of Shipping (ABS) -
Warrington

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Job details

Full-time

Qualifications

Power BI
Azure
Git
Google Cloud Platform
Tableau
SQL
Pandas
AWS
Docker
Bachelor's degree
Machine learning
Natural language processing
Data science
Communication skills
Python

Full job description

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 (e.g., 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 (e.g., Data Science, Computer Science, Engineering, Mathematics, Statistics) or related field, or equivalent practical experience.
2+ 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 (e.g., 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 (e.g., 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 (e.g., 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 (e.g., classification, forecasting, document information extraction, OCR, LLMs, or search/retrieval systems).
Exposure to cloud platforms (Azure/AWS/GCP), ML tooling (e.g., 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.

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Junior Data Scientist - AI Practice Team

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