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- Tasks: Join our team to tackle geological challenges using advanced data science techniques.
- Company: Be part of a leading global energy provider that values innovation and growth.
- Benefits: Competitive salary, career development opportunities, and a supportive work environment.
- Why this job: Make a real impact by unlocking insights from complex subsurface data.
- Qualifications: Honours degree in data science and 2 years of relevant experience required.
- Other info: Collaborative culture with excellent opportunities for career advancement.
The predicted salary is between 36000 - 60000 £ per year.
We are looking for the right people - people who want to innovate, achieve, grow and lead. We attract and retain the best talent by investing in our employees and empowering them to develop themselves and their careers. Experience the challenges, rewards and opportunity of working for one of the world's largest providers of products and services to the global energy industry.
About the Role
We are seeking a skilled and motivated Data Scientist to join our Subsurface team at our Abingdon office in Oxfordshire. This is a unique opportunity to apply advanced data science techniques to geological and geospatial challenges, helping us unlock insights from complex subsurface data.
Key Responsibilities
- Develop robust Python pipelines for data manipulation using NLP and Foundation Models
- Apply geospatial libraries and techniques to subsurface geological datasets
- Implement secure coding practices and manage version control using Git
- Work with cloud platforms (AWS and Azure) to scale data workflows and manage infrastructure
- Optimize database performance and spatial queries using PostgreSQL/PostGIS
Required Qualifications
- Honors degree (2:1 or above) in data science or related field.
- Minimum of 2 years related work experience
Essential Skills
- Proficiency in Python, with a strong grasp of Python best practices
- Experience using Git for version control and collaboration
- Experience in use of ML, NLP and Foundation Models in ETL pipelines
- Knowledge of secure coding principles
- Familiarity with geospatial libraries such as GeoPandas, Shapely, and GDAL
- Knowledge of PostgreSQL/PostGIS for spatial data management
- Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and data science tools (e.g., Jupyter, Pandas, NumPy)
- Ability to design, train, and evaluate supervised and unsupervised learning algorithms
- Experience working with large datasets, including data preprocessing
- Excellent communication skills, both written and verbal English, with the ability to communicate complex ideas clearly
- Strong teamwork and interpersonal skills, with a collaborative and agile mindset
- Self-motivated, detail-oriented, and capable of managing multiple tasks
Desirable Skills
- Knowledge of geological or subsurface data domains
- Experience developing AI models across domains such as natural language processing, computer vision, or predictive analytics
- Experience with containerization tools such as Docker and Kubernetes
- Familiarity with CI/CD pipelines for automated deployment
- Experience with database virtualisation, including DecisionSpace integration server
- Experience with data analysis applications from the Neftex Predictions portfolio
Halliburton is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, disability, genetic information, pregnancy, citizenship, marital status, sex/gender, sexual preference/orientation, gender identity, age, veteran status, national origin, or any other status protected by law or regulation.
Location: 97 Jubilee Avenue, Milton Park, Abingdon, Oxfordshire, OX14 4RW, United Kingdom
Compensation Information: Compensation is competitive and commensurate with experience.
Data Scientist employer: Halliburton
Contact Detail:
Halliburton Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Network like a pro! Reach out to current employees on LinkedIn or attend industry meetups. It’s all about making connections that can help us get our foot in the door.
✨Tip Number 2
Prepare for those interviews by practising common data science questions and showcasing your projects. We want to demonstrate our skills and passion for the role, so let’s make sure we’re ready to shine!
✨Tip Number 3
Don’t forget to tailor our approach! Research the company and its values, and align our answers to show how we fit into their culture. This will help us stand out as the right people they’re looking for.
✨Tip Number 4
Apply through our website! It’s the best way to ensure our application gets seen. Plus, it shows we’re genuinely interested in being part of the team at StudySmarter.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Scientist role. Highlight your experience with Python, Git, and any relevant projects that showcase your skills in ML and NLP. We want to see how you can innovate and lead in this position!
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. Let us know how you plan to grow and achieve with us.
Showcase Your Projects: If you've worked on any cool data science projects, make sure to mention them! Whether it's using geospatial libraries or building ML models, we love seeing practical applications of your skills. Share links if possible!
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 to join our team!
How to prepare for a job interview at Halliburton
✨Know Your Data Science Stuff
Make sure you brush up on your Python skills and be ready to discuss your experience with ML, NLP, and Foundation Models. Be prepared to explain how you've applied these techniques in real-world scenarios, especially in ETL pipelines.
✨Show Off Your Geospatial Knowledge
Since the role involves working with geological datasets, it’s crucial to demonstrate your familiarity with geospatial libraries like GeoPandas and Shapely. Have examples ready that showcase how you've used these tools to solve complex problems.
✨Talk About Teamwork
This company values collaboration, so be ready to share experiences where you worked effectively in a team. Highlight your communication skills and how you’ve contributed to group projects, especially in an agile environment.
✨Prepare for Technical Questions
Expect some technical questions related to database management and cloud platforms. Brush up on PostgreSQL/PostGIS and be ready to discuss your experience with AWS or Azure. It’s also a good idea to understand secure coding practices and version control with Git.
