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- Tasks: Build and own ML models on large, messy datasets while designing impactful experiments.
- Company: Join a forward-thinking data function in Abu Dhabi with relocation support.
- Benefits: Competitive salary, education allowance, comprehensive healthcare, and generous leave.
- Why this job: Make a real impact with your skills in a dynamic, supportive environment.
- Qualifications: Strong foundations in statistics, Python coding, and experience with large datasets.
- Other info: Enjoy a sustainable work-life balance with short-term remote options.
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)
- Market, macroeconomic, or financial time-series data
- Commodities, energy, or asset-level datasets
- Equities-related data (earnings, filings, corporate disclosures)
- Alternative or unstructured data used in modelling or forecasting (e.g. transactions, text, imagery, sensor data)
- Forecasting, scenario analysis, optimisation, or risk-aware modelling
Compensation & 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 dana@durlstonpartners.com
Senior Data Scientist in England employer: Durlston Partners
Contact Detail:
Durlston Partners Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist in England
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect on LinkedIn. 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.
✨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 they relate to the role you're applying for.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Senior Data Scientist in England
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 in statistics and Python.
Craft a Compelling Summary: In your brief summary, focus on your most relevant experiences and achievements. This is your chance to shine, so make it engaging and directly related to the job description!
Showcase Your Impact: When detailing your past work, emphasise the impact of your contributions. Mention specific models you've built or systems you've implemented that made a difference in your previous roles.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you don’t miss out on any important updates!
How to prepare for a job interview at Durlston Partners
✨Know Your Data Inside Out
As a Senior Data Scientist, you’ll be working with large, messy datasets. Make sure you’re familiar with the types of data mentioned in the job description, like financial time-series or alternative data. Prepare to discuss your past experiences with these datasets and how you’ve tackled challenges related to them.
✨Showcase Your ML Skills
Be ready to dive deep into your machine learning expertise. Bring examples of models you've built and explain the thought process behind them. Highlight any production systems you've shipped and the impact they had. This is your chance to demonstrate your hands-on experience and technical prowess.
✨Prepare for Technical Questions
Expect some technical grilling during the interview. Brush up on statistics, probability, and applied machine learning concepts. Practice explaining complex ideas in simple terms, as you may need to communicate your work to non-technical stakeholders. Being clear and concise will set you apart.
✨Ask Insightful Questions
Interviews are a two-way street! Prepare thoughtful questions about the company’s data function, their current projects, and how they measure success. This shows your genuine interest in the role and helps you assess if it’s the right fit for you. Plus, it gives you a chance to engage with your interviewers.
