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- Tasks: Build and own ML models on large, messy datasets while designing experiments.
- Company: Join a leading investment management firm in Abu Dhabi with a focus on data innovation.
- Benefits: Competitive salary, education allowance, 30 days leave, and comprehensive healthcare for you and your family.
- Why this job: Make a real impact by working on cutting-edge data projects in a supportive environment.
- Qualifications: Strong stats background, fluent in Python, and experience with large datasets.
- Other info: Enjoy a sustainable work model with short-term remote options and generous public holidays.
The predicted salary is between 100000 - 200000 ÂŁ per year.
This range is provided by Durlston Partners. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
Location: Abu Dhabi, UAE (relocation support provided)
Compensation: £120,000–£300,000 total compensation (fully guaranteed, all‑in)
The Role: We are building a centralised data function supporting quantitative research and development teams. The role focuses on large‑scale unstructured and alternative data and applies statistical and machine learning methods. Much of the work is greenfield, with responsibility for defining data, modelling, and experimentation standards from first principles.
What You’ll Do:
- Build and own ML models and data workflows on large, messy datasets
- Design experiments to assess data structure, signal quality, and robustness
- Develop forecasting, modelling, or optimisation systems that inform decisions
- Analyse model behaviour, regime shifts, drift, and failure modes
- Design repeatable data and experimentation systems
- Translate modelling work into production‑grade components
- Own models end‑to‑end, including monitoring and iteration
Who Thrives Here:
- Strong foundations in statistics, probability, and applied machine learning
- Fluent Python with experience writing production‑quality, testable code
- Hands‑on experience with large, noisy datasets
- Demonstrated impact through shipped models, production systems, or original work
Relevant Experience (one or more):
- Commodities, energy, or asset‑level datasets
- Alternative or unstructured data used in modelling or forecasting (e.g. transactions, text, imagery, sensor data)
Benefits:
- Fully guaranteed, competitive compensation
- Education allowance for dependent children
- 30 working days of annual leave
- Comprehensive healthcare for employee and family
- Business class relocation flights
- Joining and departure allowances
The role is on‑site in Abu Dhabi. Short‑term remote work during the peak summer months is supported, along with generous leave and public holidays. The working model is designed for long‑term sustainability and family life.
How to Apply: Send your CV and a brief summary of relevant experience to.
Seniority level: Mid‑Senior level
Employment type: Full‑time
Job function: Engineering and Research
Industries: Investment Management, Financial Services, and Capital Markets
Senior Data Scientist in London employer: Durlston Partners
Contact Detail:
Durlston Partners Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with fellow data enthusiasts. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving large datasets and machine learning models. 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 skills and understanding the latest trends in data science. Practice explaining your past projects and how you've tackled challenges—this will help you shine during those crucial conversations.
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining us at StudySmarter. Tailor your application to highlight your relevant experience and show us why you're the perfect fit for the Senior Data Scientist role.
We think you need these skills to ace Senior Data Scientist in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Senior Data Scientist role. Highlight your experience with large datasets, machine learning models, and any relevant projects that showcase your skills. We want to see how you can bring value to our team!
Craft a Compelling Summary: When writing your summary, focus on your key achievements and how they relate to the job description. Use clear and concise language to demonstrate your expertise in statistics and applied machine learning. This is your chance to shine!
Showcase Your Projects: Include specific examples of your work with unstructured data or any impactful models you've built. We love seeing real-world applications of your skills, so don’t hold back on sharing your successes and learnings!
Apply Through Our Website: We encourage you to apply directly through our website for a smoother application process. It helps us keep track of your application and ensures you’re considered for the role. Let’s get started on this journey together!
How to prepare for a job interview at Durlston Partners
✨Know Your Data Inside Out
Make sure you’re well-versed in the types of unstructured and alternative data relevant to the role. Brush up on your experience with large datasets and be ready to discuss specific projects where you’ve applied statistical and machine learning methods.
✨Showcase Your ML Models
Prepare to talk about the machine learning models you've built and owned. Highlight the end-to-end process, from data collection to monitoring model performance. Be ready to share examples of how your models have made a tangible impact.
✨Experimentation is Key
Since the role involves designing experiments, come prepared with examples of how you’ve assessed data structure and signal quality in past projects. Discuss your approach to ensuring robustness and reliability in your findings.
✨Be Ready for Technical Questions
Expect technical questions that test your foundations in statistics and probability. Brush up on Python coding skills, especially in writing production-quality code. Practise explaining complex concepts in a clear and concise manner.
