Senior Data Scientist - AI/ML Quantitative Interpretation

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.

Job Duties and Qualifications

About the Role:

We are seeking a highly motivated and experienced Senior Data Scientist with a strong background in advanced AI/ML techniques, including Physics-Informed Neural Networks (PINNs), Reinforcement Learning, and Generative Adversarial Networks (GANs). The ideal candidate will have a proven track record of applying these methods to solve complex problems within the oil and gas industry or a closely related field (e.g., energy, mining, utilities). This role offers a unique opportunity to contribute to cutting-edge research and development, driving innovation and efficiency within our organization.

Responsibilities:

1.Develop and implement advanced AI/ML models, including PINNs, Reinforcement Learning algorithms, and GANs, to address challenges in areas such as:
a. Reservoir Simulation & Optimization
b. Production Forecasting & Optimization
c. Predictive Maintenance
d. Exploration & Resource Assessment
e. Field Development Planning
2. Collaborate with domain experts (geologists, engineers, etc.) to understand business needs and translate them into data science solutions.
3. Design and conduct experiments to evaluate model performance, identify areas for improvement, and ensure robustness.
4. Stay abreast of the latest advancements in AI/ML and explore their potential applications within the oil and gas domain.
5. Contribute to the development of intellectual property and publish research findings in relevant journals and conferences.
6. Mentor junior data scientists and foster a culture of innovation within the team.
7. Work closely with product engineering teams to productionize developed AI/ML solutions, ensuring seamless integration with existing internal software and platforms.

Knowledge, Skills, and Abilities

1.PhD in Computer Science, Applied Mathematics, Physics, Engineering, or a related field.
2.5+ years of experience applying advanced AI/ML techniques in the oil and gas industry or a closely related field.
3.Strong theoretical understanding and practical experience with PINNs, Reinforcement Learning, and GANs.
4.Expert level proficiency in Python and relevant machine learning libraries (e.g., TensorFlow, PyTorch)
5.Experience with data analysis and visualization tools.
6.Excellent communication and interpersonal skills, with the ability to explain complex technical concepts to both technical and non-technical audiences.

Good to have:

• Experience with cloud computing platforms (e.g., AWS, Azure, GCP).
• Familiarity with big data technologies (e.g., Hadoop, Spark).
• Contributions to open-source projects or publications in top-tier AI/ML conferences.

Benefits:

• Opportunity to work on challenging and impactful projects.
• Collaborative and supportive work environment.
• Access to cutting-edge technologies and resources.
• Professional development and growth opportunities.

 Minimum 5+ years of Experience

Type: Full-Time
Location:  Bangalore, India

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

6th Floor, Hibiscus Tower 2 Bu, Bangalore, Karnataka, 560103, India

Job Details

Requisition Number: 194971  
Experience Level: Experienced Hire 
Job Family: Engineering/Science/Technology 
Product Service Line: Landmark Software & Services   
Full Time / Part Time: Full Time

Additional Locations for this position: 

Compensation Information
Compensation is competitive and commensurate with experience.