Data Scientist

About V.Group

V. Group is a global leader in ship management and marine services, adding value to a vessel’s operations through 24/7 services around the world. The company covers crew management, recruitment, quality ship management, technical services, and commercial support, drawing on unrivaled industry knowledge and a performance‑assured approach. Its values – We Care, We Collaborate, We Challenge, We are Consistent, We Commit and Deliver – form the core of its strategy of investing in talent and delivering great service to internal and external stakeholders.

The Data Scientist will support all teams within the company, at all levels, by extracting insights from data to inform smarter, faster decisions and reporting. The focus is on applying data mining techniques, conducting statistical analysis, and building high‑quality prediction systems integrated with the company’s Business Intelligence platform and other systems.

• Data mining using state‑of‑the‑art methods
• Extending company data with third‑party information when needed
• Enhancing data collection procedures to gather relevant information for analytic systems
• Processing, cleansing, and verifying the integrity of data used for analysis
• Conducting ad‑hoc analysis and presenting results clearly
• Creating automated anomaly detection systems and continuously tracking their performance

V. Group offers a market‑leading salary and benefits package, alongside significant opportunities for career growth and personal development. This role provides a chance to join a true leader in the maritime sector that has exciting plans for future growth.

• Bachelor’s and/or Master’s degree in Statistics, Mathematics, Computer Science, or another quantitative field
• 3 – 5 years of experience manipulating data sets and building statistical models
• Strong problem‑solving skills
• Experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights from large data sets
• Experience working with and creating data architectures
• Experience with Excel, PowerPoint, Power
  
  BI, and SQL
• Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real‑world advantages and drawbacks

• Familiarity with Java or C++
• Basic understanding of the maritime industry
• Basic understanding of supply chain management
• Experience on similar projects in the past is an advantage

01 Feb 2026

Mid‑Senior level

Full‑time

Engineering and Information Technology

Maritime Transportation

Glasgow, Scotland, United Kingdom