At a Glance
- Tasks: Lead the design and delivery of AI solutions using real-world datasets.
- Company: Join a forward-thinking AI Practice Team in a dynamic tech environment.
- Benefits: Enjoy competitive salary, remote flexibility, and opportunities for professional growth.
- Why this job: Shape the future of AI while mentoring junior talent and making impactful decisions.
- Qualifications: STEM degree and 5+ years of data science experience required.
- Other info: Collaborative culture with excellent career advancement opportunities.
The predicted salary is between 48000 - 72000 £ per year.
We are seeking an exceptional Senior Data Scientist to join us full-time in our Artificial Intelligence (AI) Practice Team, Europe. In this role, you will lead the design and delivery of analytics and machine learning solutions across policy, data, and document-centric AI engagements, working with complex real-world datasets from industrial and asset-intensive domains. You will partner closely with consultants, domain experts, and junior data scientists to turn client data into robust models, reusable assets, and decision-ready insights. Based in Warrington or London England with some remote flexibility, you will help shape our technical approaches, uplift data science practices, and ensure solutions are production-aware and business-relevant.
What You Will Do:
- Lead the preparation, exploration, and analysis of client data (tabular, time-series, and document-based) to enable robust modeling, feature engineering, and insight generation.
- Design, implement, and validate machine learning models and analytics pipelines, including problem framing, model selection, evaluation, and iteration for real-world performance.
- Drive advanced use of NLP and document understanding techniques to extract, transform, and enrich information from reports, PDFs, logs, and other unstructured sources.
- Build and maintain clear, impactful dashboards, reports, and visualizations (in Python, Power BI, or similar tools) to communicate findings to consultants and client stakeholders.
- Collaborate with consultants and domain experts to translate business problems into analytical solutions, articulate trade-offs, and present recommendations to technical and non-technical audiences.
- Ensure technical quality, reproducibility, and governance by establishing good practices for code, documentation, data management, and model tracking across projects.
- Mentor and support junior data scientists, providing guidance on methods, tooling, and best practices, and reviewing their work for quality and consistency.
What You Will Need:
- Education and Experience: Bachelor’s degree in a STEM discipline (Data Science, Computer Science, Engineering, Mathematics, Statistics) or related field; Master’s degree preferred or equivalent experience. + years of experience applying data science and machine learning in professional settings, including end-to-end delivery of analytics/ML solutions. Proven track record working with real-world, messy datasets (including unstructured/document data) across the full lifecycle: data preparation, modeling, evaluation, and deployment handoff. Experience leading or owning significant workstreams within AI/ML or analytics projects, ideally in consulting, industrial, or asset-intensive environments. Practical experience working with cloud-based and modern data platforms (Azure, AWS, GCP, Databricks) and integrating with enterprise data sources and workflows.
- Knowledge, Skills, and Abilities: Deep proficiency in Python for data science (pandas, scikit-learn, and related libraries) and strong SQL skills for working with relational and analytical data stores. Strong grounding in statistics, machine learning, and model evaluation, including supervised/unsupervised methods, feature engineering, and performance diagnostics. Hands-on experience with NLP and document understanding (text preprocessing, embeddings, classification, information extraction, transformers/LLMs) applied to real datasets. Ability to design and implement robust, maintainable analytics and ML pipelines, using notebooks and production-ready code with Git-based version control. Familiarity with modern data and ML tooling (Databricks, MLflow, Docker, CI/CD for data/ML) and good practices for experiment tracking and reproducibility. Proficiency with BI/visualization tools (Power BI, Tableau) and data storytelling skills to communicate complex analytical results to non-technical stakeholders. Excellent communication and stakeholder engagement skills, with the ability to frame analytical approaches, explain trade-offs, and align solutions with business objectives. Proven ability to work across multiple projects, manage priorities, and operate in a fast-moving, consulting-style environment, while mentoring junior team members.
Nice to have: exposure to industrial, maritime, or asset-intensive domains, or prior experience in AI consulting or client-facing roles. Must hold a valid right to work status in the UK.
This role reports to the Project Manager and does not include direct reports.
Senior Data Scientist - AI Practice Team in London employer: American Bureau of Shipping
Contact Detail:
American Bureau of Shipping Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist - AI Practice Team in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the data science field, especially those who work in AI or consulting. A friendly chat can lead to insider info about job openings that aren't even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your best projects, especially those involving machine learning and NLP. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Be ready to discuss your experience with real-world datasets and how you've tackled complex challenges in previous roles.
✨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 and engaged with our company.
We think you need these skills to ace Senior Data Scientist - AI Practice Team in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Senior Data Scientist role. Highlight your experience with machine learning, data preparation, and any relevant projects you've led. We want to see how you can bring value to our AI Practice Team!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to tell us why you're passionate about data science and how your background aligns with our needs. Don't forget to mention specific projects or achievements that demonstrate your expertise in analytics and machine learning.
Showcase Your Technical Skills: Since this role involves a lot of technical work, make sure to highlight your proficiency in Python, SQL, and any relevant tools like Power BI or Databricks. We love seeing examples of your work, so if you have a portfolio or GitHub, include that too!
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 the initiative to connect with us directly!
How to prepare for a job interview at American Bureau of Shipping
✨Know Your Data Science Stuff
Make sure you brush up on your data science fundamentals, especially around machine learning models and NLP techniques. Be ready to discuss your experience with real-world datasets and how you've tackled messy data in the past.
✨Showcase Your Collaboration Skills
Since this role involves working closely with consultants and junior data scientists, be prepared to share examples of how you've successfully collaborated on projects. Highlight your ability to translate complex technical concepts into business-friendly language.
✨Prepare for Technical Questions
Expect some deep dives into your technical skills, particularly in Python and SQL. Brush up on your knowledge of libraries like pandas and scikit-learn, and be ready to explain your approach to building and validating machine learning models.
✨Demonstrate Your Communication Skills
You’ll need to present findings to both technical and non-technical audiences, so practice explaining your analytical results clearly. Think about how you can use visualisation tools like Power BI to enhance your storytelling during the interview.