At a Glance
- Tasks: Lead AI and ML projects to enhance maritime safety and sustainability.
- Company: Join RightShip, the world's largest maritime due diligence organisation.
- Benefits: Competitive salary, wellness support, and fantastic professional development opportunities.
- Why this job: Make a real impact in maritime safety while working with cutting-edge technology.
- Qualifications: 7+ years in Data Science or AI, strong analytical skills, and proficiency in Python.
- Other info: Diverse and inclusive workplace committed to your growth and success.
The predicted salary is between 60000 - 84000 £ per year.
Overview
The Company RightShip is the world’s biggest third party maritime due diligence organization, providing expertise in global safety, sustainability and social responsibility best practices. We bring together years of industry expertise with analytics and large data sets to provide our safety and environmental scoring systems, recommendations and consultancy services. Using leading data and technology, we aim to set new benchmarks in environmental protection.
What We Offer: We offer a place where you know you are contributing to an organization who are constantly working to ensure ships are safe as possible so that crew and cargo are protected. We are passionate about maritime efficiency, safety and sustainability practices. We offer generous rewards. Our base salary is competitive, we support employee wellbeing and provide our employees with a Healthy Living Allowance and our annual incentive scheme is awesome. We have some great talent who are happy to share their experience and skills to help you on your way and we are committed to professional development to make sure your career keeps growing while you’re working with us.
What makes RightShip a great place to work at: RightShip is an equal opportunity employer, and we champion diversity. Our teams are composed of individuals from different geographies, cultures, religions, ethnicities, races, genders, sexual orientations, abilities, and generations. We believe that a diversity of experiences makes us stronger—as individuals, as communities and as an organization.
Don’t meet every single requirement of this role? Still apply! Research tells us that women and underrepresented groups are less likely to apply unless they meet every single requirement. At RightShip we believe that the right hire is someone who makes an addition to our culture, rather than someone who fits in and conforms to our status quo. We want to add team members who not only value RightShip standards and workplace culture, but also bring an aspect of diversity that positively contributes to our work environment. If you are excited about this role, or about our company in general, we would love to hear from you!
Role and Responsibilities:
RightShip is scaling its use of AI from traditional ML models to advanced LLM-based reasoning systems, to support safer and more sustainable maritime operations. We are looking for a Data Scientist who can bridge both worlds: classical data science and modern AI/LLM governance.
This role is responsible for defining how models should be evaluated, monitored and governed across their lifecycle. You will work closely with domain experts, the existing AI team, data engineering and product teams to ensure our AI systems behave consistently, accurately and responsibly.
This is not an LLM-engineering or roadmap ownership role. It is a senior position focused on methodological leadership, model quality, and governance across AI and ML systems.
Major Responsibilities:
- Establish Best Practices for AI/LLM & Traditional ML Experimentation
- Develop experimental methodologies for both classical ML and LLM-based systems
- Standardise how experiments are structured, documented and compared across teams
- Create reproducible workflows for testing prompts, model versions, embeddings and classical feature models
- Ensure statistical soundness and methodological rigour in all experiments
- Own the Evaluation Framework for Model Behaviour
- Build and maintain evaluation datasets, test suites and metrics for reasoning accuracy (LLMs), classification performance (traditional models), consistency and drift, hallucination checks, edge-case handling, domain-alignment
- Continuously refine the evaluation approach as the AI team iterates on models
- Translate Domain Logic into Structured Model-Ready Logic
- Work with maritime SMEs to understand inspection logic, safety reasoning and operational decision pathways
- Convert that knowledge into classification schemas, decision flows, label definitions, reasoning templates, structured input/output rules for LLMs and ML models
- Ensure model behavior is grounded in real-work operational judgement
- Support AI Team Experimentation
- Provide guidelines, quality criteria and methodology for the AI team’s test design
- Review final experiments and highlight gaps, inconsistencies or risks
- Ensure that experimentation aligns with the governance, evaluation and lifecycle frameworks you maintain
- Maintain the benchmark suite the AI team must compare against
- Conduct Traditional Data Science & ML Work
- Contribute hands-on to classical data science tasks such as analysis of structured datasets, feature engineering and exploratory data analysis, building classification or scoring models as needed (supervised ML), supporting domain teams with insights, prototypes or predictive modelling, working with data engineers to refine the data required for ML
- Model Monitoring & Lifecycle Governance
- Build processes for ongoing monitoring of AI behaviour and model drift
- Investigate anomalies or unexpected outputs
- Identify failures rooted in data, logic, edge cases or prompt structure
- Recommend corrective actions (model retraining, logic updates, new test suites, prompt refinement)
- Maintain transparent documentation, audit trails and governance standards aligned with RightShip’s risk posture
Qualifications, Skills & Experience:
- Bachelor’s or Masters (preferred) degree in Data Science, or relevant field
- 7+ years in Data Science, Applied ML or AI-focused role
- Postgraduate studies or AI governance training is advantageous
- Curious, a critical thinker and a strong sense of logic
- Superior mathematical ability
- Strong experience building and evaluating classification and supervised ML models
- Excellent communication and presentation skills
- Excellent at establishing standards others can follow confidently
- Proficiency in Python, SQL and model evaluation frameworks
- Familiarity with MLflow (or equivalent), Vector DBs or LLM orchestration tools is a plus
- Ability to influence through expertise rather than authority
RightShip is an Equal Opportunity Employer and values diversity, enables access and promotes inclusion in our workplace. You must have the right to live and work in this location to apply for this job.
Principal Data Scientist employer: RightShip
Contact Detail:
RightShip Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Principal Data Scientist
✨Tip Number 1
Network like a pro! Reach out to people in the maritime and data science fields on LinkedIn. Join relevant groups and participate in discussions to get your name out there. You never know who might have a lead on the perfect job for you!
✨Tip Number 2
Prepare for interviews by researching RightShip and its values. Understand their commitment to safety, sustainability, and diversity. Tailor your responses to show how your experience aligns with their mission and how you can contribute to their goals.
✨Tip Number 3
Practice your technical skills! Brush up on your Python, SQL, and model evaluation frameworks. Be ready to discuss your past projects and how they relate to the role of Principal Data Scientist at RightShip. Confidence in your abilities will shine through!
✨Tip Number 4
Don’t hesitate to apply through our website! Even if you don’t meet every single requirement, we value diverse experiences and perspectives. If you’re excited about the role, we want to hear from you—so go for it!
We think you need these skills to ace Principal Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Principal Data Scientist role. Highlight your expertise in both classical data science and modern AI/LLM governance, as this is key for us at RightShip.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're excited about working at RightShip. Share your passion for maritime safety and sustainability, and how your background can contribute to our mission of making ships safer.
Showcase Your Methodological Skills: Since this role focuses on methodological leadership, be sure to include examples of how you've established best practices in AI/ML experimentation. We want to see your critical thinking and problem-solving skills in action!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity at RightShip!
How to prepare for a job interview at RightShip
✨Know Your Data Science Fundamentals
Brush up on your core data science concepts, especially around classical ML and LLMs. Be ready to discuss methodologies you've used in the past and how they can apply to RightShip's focus on safety and sustainability.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled complex data challenges. Highlight your experience with model evaluation and governance, as this role requires a strong methodological approach to ensure AI systems behave responsibly.
✨Understand the Maritime Context
Familiarise yourself with maritime operations and safety reasoning. Being able to translate domain logic into structured model-ready logic will be crucial, so demonstrate your understanding of how data science can impact this industry.
✨Communicate Clearly and Confidently
Practice articulating your thoughts clearly, especially when discussing technical concepts. RightShip values excellent communication skills, so be prepared to explain your ideas and methodologies in a way that’s accessible to both technical and non-technical stakeholders.