Data Scientist

Veson Nautical LLC
Stoke-on-Trent
2 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist (Government)

Data Scientist Placement

Data Scientist

Who We Are:


Veson Nautical is a global software and data business that provides the maritime commercial industry with a standard platform to streamline operations, offer insightful analytics, and drive unparalleled efficiency.


In this role, you will be working in Veson Nautical’s Data Science team. This is a group of experts in data science, artificial intelligence, and other quantitative disciplines, drawn from industry and academia. Its role is to transform Veson Nautical’s rich data assets into actionable intelligence.


The Opportunity

The Data Science team plays a vital role in driving innovation through research and development of data‑driven products. Working closely with product managers, software engineers, and clients, our data scientists understand commercial needs and align their research to solve high‑value problems. The team’s fundamental mission is to extract insights from data to support maritime commercial decisions.


Our Stack

The Data Science team writes applications mostly in Python, with some TypeScript and JavaScript as required. We deploy services primarily to AWS EKS via ECR and GitLab CI/CD. We commonly use SQL and GQL to access data from internal systems. We have access to cutting‑edge AI tools.


Location

This role is hybrid, with 2–3 days per week in either our London or Stoke‑on‑Trent office.


Key Responsibilities

  • Collaborate with product managers, software engineers, commercial teams, and clients to understand product requirements and translate them into relevant R&D.
  • Design and develop robust data pipelines, ensuring the efficient collection, transformation, analysis, and derivation of maritime data from various sources.
  • Apply the scientific method to measure and maximize the performance of the model, algorithm, or application being developed.
  • Use programming languages, especially Python, to build statistical models and algorithms for predictive and prescriptive analytics.
  • Create and deploy production‑ready data processing pipelines, algorithms, and applications.

Essential Skills and Experience

  • EITHER proven commercial experience in data science (to include machine learning and artificial intelligence applications).
  • OR a doctoral degree in data science or other highly quantitative discipline such as mathematics, physics, biosciences, computer science, engineering.
  • Strong programming skills in Python or other languages commonly used for data analysis and mathematical modelling (such as R, MATLAB, C and its derivatives).
  • Knowledge of the principles and practice of statistical analysis and machine learning.
  • Experience of data visualization and reporting.

Desirable Skills and Experience (not required)

  • Use of Application Programming Interfaces (APIs) for data retrieval and delivery.

We are building a diverse and inclusive workforce. If you are excited about this role but do not meet 100% of the qualifications listed above, we encourage you to apply. While we try to be thorough with our job descriptions, not everything about you as a candidate can be condensed into a list of bullet points.


More About Veson

We are a team of multi‑disciplinary professionals dedicated to making our clients successful by charting a new and innovative course for the maritime commercial industry. We invest heavily in employee development and experience to promote enthusiasm and creativity. We are a dynamic blend of engineers, scientists, artists, sailors, teachers, brokers, bankers, traders, and consultants.


Veson Nautical is a successful and rapidly growing global software company. Our clients are the world’s leading commercial maritime owners, operators, and commodity trading companies. Our solutions enable clients to identify new opportunities and make more profitable decisions. With headquarters in Boston and offices in London, Singapore, Seoul, Shanghai, Hong Kong, Oslo, Manila, Tokyo, Houston and many others, our committed team of professionals brings decades of commercial experience and technical know‑how to clients around the world.


The combination of exceptional market growth and leading market position makes this a superb opportunity for the right candidate.


#LI-Hybrid


#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.

Careers

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

Jobs

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

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

Education

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

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.