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- Tasks: Build and own ML models on large, messy datasets while designing impactful experiments.
- Company: Leading data-driven company in Abu Dhabi with a focus on innovation.
- Benefits: Competitive salary, relocation support, and opportunities for professional growth.
- Why this job: Make a real impact by working on cutting-edge data science projects.
- Qualifications: Strong foundations in statistics, Python coding, and hands-on experience with large datasets.
- Other info: Dynamic environment with greenfield projects and excellent career advancement opportunities.
The predicted salary is between 84000 - 180000 £ per year.
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
Senior Data Scientist employer: Durlston Partners
Contact Detail:
Durlston Partners Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist
✨Tip Number 1
Network like a pro! Reach out to professionals in the data science field on LinkedIn or at industry events. We can leverage our connections to get insights and maybe even referrals for that Senior Data Scientist role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your ML models and data workflows. We should highlight our hands-on experience with large datasets and any impactful projects we've completed to catch the eye of recruiters.
✨Tip Number 3
Prepare for interviews by brushing up on key concepts in statistics and machine learning. We can practice explaining our past projects and how we tackled challenges, as this will demonstrate our expertise and problem-solving skills.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. We can tailor our applications to highlight our relevant experience with unstructured data and forecasting systems, making us stand out.
We think you need these skills to ace Senior Data Scientist
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 Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data science and how your background aligns with our mission at StudySmarter. Be specific about your achievements and how they relate to the role.
Showcase Your Projects: If you've worked on interesting projects, especially those involving unstructured data or innovative modelling techniques, make sure to mention them. We love seeing real-world applications of your skills!
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It helps us keep track of applications and ensures you’re considered for the role directly!
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 large, messy datasets you’ll be working with. Brush up on your experience with unstructured data and be ready to discuss specific examples of how you've handled similar challenges in the past.
✨Showcase Your ML Skills
Prepare to talk about your experience with machine learning models. Be ready to explain the models you've built, the statistical methods you used, and how you ensured they were production-ready. Highlight any unique approaches or innovations you've implemented.
✨Experimentation is Key
Since the role involves designing experiments, think of a few scenarios where you’ve successfully assessed data structure or signal quality. Be prepared to discuss your thought process and the outcomes of those experiments.
✨Demonstrate End-to-End Ownership
Emphasise your ability to own models from start to finish. Share examples of how you've monitored model performance, iterated based on feedback, and ensured that your work had a tangible impact on decision-making.
