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- Tasks: Lead machine learning model development and deliver data-driven insights.
- Company: A leading technology company with a focus on innovation.
- Benefits: Competitive salary, travel opportunities, and professional growth.
- Why this job: Make an impact by enhancing decision-making through predictive analytics.
- Qualifications: Strong statistical skills, Python proficiency, and time series data experience.
- Other info: Opportunity for a business trip to Kuwait for hands-on experience.
The predicted salary is between 36000 - 60000 £ per year.
A leading technology company is seeking a Data Scientist in the United Kingdom to lead machine learning model development and deliver data-driven insights. The candidate will analyze operational datasets and collaborate with engineers to create predictive analytics that enhance decision-making.
Key qualifications include:
- Strong statistical skills
- Python proficiency
- Experience with time series data
Candidates should be open to a business trip to Kuwait for the first 6-12 months.
Data Scientist: Oilfield ML & Analytics (Kuwait On-site) employer: Luxoft
Contact Detail:
Luxoft Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist: Oilfield ML & Analytics (Kuwait On-site)
✨Tip Number 1
Network like a pro! Reach out to professionals in the data science field, especially those who work in oilfield analytics. Use platforms like LinkedIn to connect and engage with them; you never know who might have a lead on that perfect job!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects and predictive analytics work. This is your chance to demonstrate your Python prowess and statistical skills, so make it shine!
✨Tip Number 3
Prepare for the interview by brushing up on time series analysis and operational datasets. Be ready to discuss how you've used these in past projects, as this will show you're the right fit for the role.
✨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: Oilfield ML & Analytics (Kuwait On-site)
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your statistical skills and Python proficiency in your application. We want to see how you can apply these skills to real-world problems, especially with time series data.
Tailor Your Application: Don’t just send a generic CV and cover letter. Tailor your application to the job description, focusing on your experience with machine learning model development and predictive analytics. We love seeing candidates who take the time to connect their background to our needs.
Be Ready for Adventure: Since this role involves a business trip to Kuwait, mention your openness to travel in your application. We appreciate candidates who are excited about new experiences and challenges!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at Luxoft
✨Know Your Stats
Brush up on your statistical skills before the interview. Be ready to discuss how you’ve applied statistical methods in past projects, especially in relation to machine learning and predictive analytics.
✨Python Proficiency is Key
Make sure you can demonstrate your Python skills. Prepare to talk about specific libraries you've used for data analysis and machine learning, like Pandas or Scikit-learn, and be ready to solve a coding challenge on the spot.
✨Familiarise with Time Series Data
Since time series data is crucial for this role, review your experience with it. Be prepared to explain how you’ve handled time series analysis in previous projects and the techniques you used to derive insights.
✨Be Open About Travel
Since the role involves a business trip to Kuwait, express your willingness to travel. Show enthusiasm for the opportunity to work on-site and collaborate with engineers in a different environment.
