Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Lead the development of machine learning models and data-driven insights for Digital Oilfield systems.
- Company: Join a forward-thinking company in the oil and gas sector.
- Benefits: Competitive salary, hands-on experience, and potential travel opportunities.
- Why this job: Make a real impact by transforming complex data into actionable intelligence.
- Qualifications: Strong statistical background, Python proficiency, and teamwork skills required.
- Other info: Exciting opportunity for career growth with a business trip to Kuwait.
The predicted salary is between 36000 - 60000 £ per year.
We are looking for a hands-on Data Scientist to lead the development of machine learning models and data-driven insights for Digital Oilfield (DOF) systems. This role requires a strong foundation in data science and statistical modeling, with the ability to transform noisy, real-world oilfield data into actionable intelligence for engineering teams. The candidate will work alongside production engineers, software developers, and ML engineers to design, validate, and operationalize predictive and prescriptive analytics that support key decisions in subsurface and surface operations. Oil & gas experience is a strong asset but not mandatory; the ideal candidate brings analytical rigor and problem-solving expertise to solve complex field challenges.
Responsibilities
- Analyze diverse operational datasets (time series, tabular, sensor logs, etc.) to extract insights and guide model development.
- Build and evaluate ML models for forecasting, anomaly detection, pattern recognition, and classification.
- Work with engineers to define KPIs and convert domain-specific questions into quantifiable modeling tasks.
- Design meaningful visualizations and dashboards to communicate model outputs clearly.
- Collaborate with ML Ops and software teams to deploy models into production environments and monitor performance.
- Business trip to Kuwait for first 6-12 months. On-site.
Skills
Must have
- Strong statistical background and data science expertise with real-world datasets.
- Proficient in Python (NumPy, pandas, scikit-learn, XGBoost, etc.); SQL fluency and data wrangling skills.
- Experience working with large, messy, or multivariate time series data.
- Ability to communicate complex model behavior to engineers and stakeholders.
- Comfortable working in cross-functional teams with domain and technical experts.
- Ready for a long term business trip to Kuwait for first 6-12 months.
Nice to have
- Oilfield data exposure (e.g., well data, reservoir simulations, production logs) or interest in industrial applications.
- Familiarity with DOF systems or production optimization frameworks.
- Exposure to LLMs, NLP techniques, or agent-based AI for enhancing technical workflows.
- Cloud familiarity (Azure preferred); knowledge of ML platforms (e.g., Azure ML, Databricks).
- Azure Data Scientist Associate or Microsoft AI Fundamentals certification is a plus.
- AWS cloud knowledge is welcome but not required.
Data Scientist (on-site) employer: Luxoft
Contact Detail:
Luxoft Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist (on-site)
✨Tip Number 1
Network like a pro! Reach out to professionals in the oil and gas sector, especially those working with data science. Attend industry meetups or webinars to make connections that could lead to job opportunities.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving machine learning models or data visualisations. This will give potential employers a taste of what you can do with real-world datasets.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Be ready to discuss how you've tackled complex data challenges in the past and how you can apply that experience to their operations.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Data Scientist (on-site)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your data science skills and experience relevant to the role. We want to see how you've tackled real-world datasets and any machine learning projects you've led.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Tell us why you're passionate about data science and how you can contribute to our Digital Oilfield systems. Be specific about your experiences and what excites you about this role.
Showcase Your Technical Skills: We love seeing your technical prowess! Include examples of your work with Python, SQL, and any ML models you've built. If you've worked with messy time series data, let us know how you handled it!
Apply Through Our Website: Don't forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. We can't wait to see what you bring to the table!
How to prepare for a job interview at Luxoft
✨Know Your Data Science Fundamentals
Brush up on your statistical modelling and data science principles. Be ready to discuss how you’ve applied these concepts in real-world scenarios, especially with messy datasets. This will show your analytical rigor and problem-solving skills.
✨Showcase Your Technical Skills
Make sure you’re comfortable discussing your experience with Python libraries like NumPy, pandas, and scikit-learn. Prepare examples of how you've used SQL for data wrangling and how you’ve built ML models for tasks like forecasting or anomaly detection.
✨Communicate Clearly
Practice explaining complex model behaviours in simple terms. You’ll need to collaborate with engineers and stakeholders, so being able to convey your insights clearly is crucial. Think about how you can present your findings visually as well.
✨Be Ready for the Kuwait Adventure
Since this role involves a business trip to Kuwait, be prepared to discuss your willingness to relocate and how you plan to adapt to a new environment. Show enthusiasm for the opportunity and any research you’ve done about working in the oilfield sector.
