At a Glance
- Tasks: Build advanced AI solutions for maritime intelligence using rich datasets.
- Company: Join Pole Star, a leader in maritime intelligence with a diverse global team.
- Benefits: Enjoy flexible working, private healthcare, gym programs, and unlimited learning opportunities.
- Other info: Collaborative environment with a focus on innovation and career growth.
- Why this job: Make a real impact in maritime technology while developing cutting-edge AI solutions.
- Qualifications: 4+ years in data science, strong Python and SQL skills, experience with AWS.
The predicted salary is between 60000 - 80000 € per year.
About Pole Star: As the leader in maritime intelligence, Pole Star empowers better decision‑making and protects clients’ business interests, assets, seafarers, vessels, cargo, infrastructure, investments, profitability, and reputation – through high‑performance, cyber‑secure solutions supported by continuous technological innovation. We have offices in London, USA, Singapore, Hong Kong and Panama, alongside presence in Australia. Teams are made up of over 19 nationalities, speaking 25 different languages.
The Opportunity: As a Data Scientist, you will build advanced analytical, machine‑learning, and agentic AI solutions that power Pole Star’s maritime intelligence products and internal decision‑making. You will work with rich time‑series and geospatial datasets, including vessel positional data (AIS, RF and other sources), geospatial zones, and weather/ocean models, helping to turn these into high‑value derived datasets and signals. You will contribute to Pole Star’s AI/ML roadmap: identifying high‑impact use cases, experimenting with models (including LLMs and agentic AI), and working with Data Engineers and Product teams to move successful solutions into production in AWS.
Responsibilities:
- Collaborate on Pole Star’s AI/ML roadmap and strategy, aligning data science work with product and business priorities.
- Develop and deploy machine learning and agentic AI use cases on maritime datasets (AIS, RF, geospatial, NWP, product/operational data).
- Perform feature engineering and model experimentation using Python and (where appropriate) Spark on complex time‑series and geospatial data.
- Work with Data Engineers to productionise models and data products in AWS (batch and, where relevant, streaming/near real‑time).
- Support the design and validation of data quality and reconciliation logic (e.g. AIS vs RF vs other positional sources), including quality scores and anomaly indicators.
- Validate, monitor, and improve model performance, setting up appropriate evaluation metrics and monitoring.
- Analyse and explain AI/ML solutions to technical and non‑technical stakeholders, maintaining high ethical and governance standards.
- Document models, experiments, and lessons learned in code repositories and internal knowledge bases.
- Support analytics and BI teams with advanced modelling and statistical analysis for key business questions.
Required Skills:
- 4+ years of experience in a Data Scientist role, ideally in maritime, logistics, transportation or other complex time‑series/geospatial domains.
- Strong Python programming skills for data analysis and modelling.
- Strong SQL skills and experience with analytical data stores.
- Experience with core ML libraries/frameworks (e.g. scikit‑learn, TensorFlow and/or PyTorch, pandas, NumPy, SciPy).
- Experience working with time‑series and/or geospatial data.
- Experience working in AWS environments (e.g. S3, Glue, EMR/Databricks, SageMaker or similar).
- Experience with notebook‑driven development (Jupyter, VS Code, or similar) and Git‑based workflows.
- Solid foundation in statistics and machine learning, including model evaluation and validation.
- Strong communication skills to present findings and explain model behaviour to technical and non‑technical stakeholders.
Additional Skills (Nice to have):
- Experience with LLMs, NLP and/or agentic AI solutions (e.g. Hugging Face or similar ecosystems).
- Experience with Spark or PySpark for large‑scale data processing.
- Exposure to BI platforms (QuickSight, Tableau or similar).
- Experience with ML/AI Ops practices (model lifecycle, CI/CD for ML, monitoring).
- Experience with maritime intelligence, AIS data, RF signal data or NWP/metocean data.
- Experience with real‑time analytics platforms (e.g. Tinybird or similar).
- Experience with additional languages (e.g. Scala, R, Java, C++), where relevant.
Education/Certifications:
- Bachelor’s degree in Computer Science, Computer Engineering, Statistics, Mathematics, Electronics & Communications Engineering, or a related field; OR Master’s degree in Data Science, Artificial Intelligence, or a related discipline.
- Certifications in public cloud services related to Machine Learning / Data Science (AWS preferred) are an advantage.
Employee Benefits:
- Hybrid/Flexible working
- Flexible Benefits Package Including:
- Private healthcare.
- Dental, Optical
- Salary sacrifice schemes
- Gym and wellness programs
- Childcare vouchers
- Buy/Sell holidays
- Cycle to work scheme
- Medicash health cash plan
- Home and tech scheme
- Life insurance, company funded to 3x salary
- Employee assistance program
- 25 days annual leave
- 5 wellbeing days
- Volunteering leave (2 days annually)
- Up to a 5% matching pension
- Unlimited learning and development opportunities
- Refer‑a‑friend recruitment bonus
Data Scientist - Maritime Technology in London employer: Pole Star Global
Pole Star is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration among a diverse team of over 19 nationalities. As a Data Scientist in maritime technology, you will benefit from flexible working arrangements, a comprehensive benefits package including private healthcare and wellness programmes, and unlimited opportunities for professional growth, all while contributing to cutting-edge solutions that enhance maritime intelligence.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist - Maritime Technology in London
✨Tip Number 1
Network like a pro! Reach out to people in the maritime tech space on LinkedIn or at industry events. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data science projects, especially those related to time-series and geospatial data. This will give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your Python and SQL skills. Be ready to discuss your experience with machine learning frameworks and how you've tackled complex datasets in the past.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Data Scientist - Maritime Technology in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Scientist role at Pole Star. Highlight your experience with time-series and geospatial data, as well as your Python and SQL skills. We want to see how your background aligns with our maritime technology focus!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about maritime intelligence and how your skills can contribute to our AI/ML roadmap. Keep it engaging and relevant to the job description.
Showcase Your Projects:If you've worked on any relevant projects, especially those involving machine learning or data analysis, make sure to mention them. We love seeing practical examples of your work, so include links to your GitHub or any other portfolios if you have them!
Apply Through Our Website:We encourage you to apply directly through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to keep track of your application status. Plus, we love seeing candidates who take that extra step!
How to prepare for a job interview at Pole Star Global
✨Know Your Data
Make sure you’re well-versed in the types of datasets you'll be working with, especially time-series and geospatial data. Brush up on your experience with vessel positional data and how it relates to maritime intelligence. Being able to discuss specific examples from your past work will show that you understand the domain.
✨Showcase Your Technical Skills
Prepare to demonstrate your Python programming skills and familiarity with core ML libraries like scikit-learn or TensorFlow. You might be asked to solve a problem on the spot, so practice coding challenges related to data analysis and machine learning to feel confident during the interview.
✨Communicate Clearly
Since you'll need to explain complex AI/ML solutions to both technical and non-technical stakeholders, practice articulating your thought process clearly. Use simple language to describe your models and findings, and be ready to answer questions about your approach and decisions.
✨Align with Their Vision
Research Pole Star’s AI/ML roadmap and think about how your experience aligns with their goals. Be prepared to discuss how you can contribute to their projects and what high-impact use cases you would prioritise. Showing that you understand their business priorities will set you apart.
