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- Tasks: Build and own ML models on large, messy datasets while designing impactful experiments.
- Company: Dynamic data-driven company based in Abu Dhabi with a focus on innovation.
- Benefits: Competitive salary, education allowance, 30 days leave, and comprehensive healthcare.
- Why this job: Make a real impact in a greenfield role with cutting-edge data science techniques.
- Qualifications: Strong stats foundation, fluent in Python, and hands-on experience with large datasets.
- Other info: On-site role with short-term remote work options and a family-friendly working model.
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
- 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 Newcastle upon Tyne employer: Durlston Partners
Contact Detail:
Durlston Partners Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist in Newcastle upon Tyne
✨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 how you can contribute to our mission.
We think you need these skills to ace Senior Data Scientist in Newcastle upon Tyne
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 clear how your background aligns with what we’re looking for in this role.
Showcase Your Impact: When detailing your past work, emphasise the impact of your contributions. Whether it’s through shipped models or production systems, we want to see how you’ve 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 from us!
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 can discuss your experience with similar data types and how you've tackled challenges in the past. Be ready to share specific examples of models you've built and the impact they had.
✨Brush Up on Your ML Techniques
Since the role involves applying statistical and machine learning methods, ensure you're well-versed in the latest techniques. Prepare to explain your approach to model building, experimentation, and how you handle model monitoring and iteration. This will show your depth of knowledge and practical skills.
✨Demonstrate Your Problem-Solving Skills
Expect to face scenario-based questions that assess your analytical thinking. Think about how you've designed experiments or optimised systems in previous roles. Be ready to walk through your thought process and the decisions you made along the way.
✨Cultural Fit is Key
This company values strong foundations in statistics and applied machine learning, but they also want someone who thrives in their collaborative environment. Research their culture and be prepared to discuss how your values align with theirs. Show enthusiasm for the role and the team!
