Job Description
Summary
Halliburton, a global leader in the energy sector, is hiring an experienced Technical Advisor – Data Science in Bengaluru, Karnataka. This high-impact position plays a strategic role in delivering enterprise-wide data science solutions, leading advanced analytics initiatives, and shaping the future of AI/ML and data strategy within the organization. Ideal for candidates with 8+ years of experience in data science, big data engineering, and predictive modeling, this opportunity offers significant career growth and global exposure at one of the world’s largest energy technology companies.
Job Details at a Glance
| Job Title | Technical Advisor – Data Science |
|---|---|
| Company | Halliburton |
| Location | Bengaluru, Karnataka, India |
| Job ID | 202420 |
| Department | Engineering / Science / Technology |
| Business Unit | Landmark Software & Services |
| Experience Level | Experienced Hire (8+ years) |
| Education Required | Bachelor’s in STEM (Master’s or Ph.D. preferred) |
| Work Type | Full-Time |
| Posted Date | 09 September 2025 |
| Compensation | Competitive and commensurate with experience |
Key Responsibilities
As the Data Science Technical Advisor at Halliburton Bengaluru, you will:
Data Strategy & Project Leadership
- Lead multiple large-scale data science projects across departments.
- Develop end-to-end data analytics solutions tailored to business goals.
- Identify and evaluate emerging data technologies for enterprise adoption.
Data Engineering & Analysis
- Master and map internal data sources; define standards for data extraction, cleaning, and storage.
- Build and maintain scalable data dictionaries and metadata repositories.
- Drive excellence in data collection and transformation workflows.
Advanced Modeling & Innovation
- Guide the design, training, and deployment of advanced machine learning models.
- Evaluate model performance, robustness, and scalability across various use cases.
- Promote innovation by testing and integrating cutting-edge AI/ML tools and platforms.
Process & Policy Development
- Shape internal data science best practices, model governance, and documentation standards.
- Recommend improvements to analytical tools, technologies, and operational pipelines.
Cross-Functional Collaboration
- Collaborate with engineering, business, and IT teams to drive data-centric decision-making.
- Present findings to executive leadership and key stakeholders.
Required Skills & Qualifications
Education
- Bachelor’s degree in STEM (Science, Technology, Engineering, Mathematics) – Required.
- Master’s or Ph.D. in Data Science, AI, Machine Learning, or related field – Preferred.
Experience
- Minimum 8 years of hands-on experience in data science, analytics, or machine learning.
- Proven track record of leading enterprise-level data projects from concept to deployment.
Technical Expertise
- Strong command over Python, R, SQL, and data visualization tools (e.g., Power BI, Tableau).
- Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
- Knowledge of data platforms like Hadoop, Spark, AWS, Azure, or Google Cloud.
- Proficiency in data modeling, predictive analytics, and statistical analysis.
Soft Skills
- Excellent communication and stakeholder management abilities.
- Strong analytical mindset with leadership in technical mentoring.
- Curiosity-driven and innovation-focused problem solver.
Why Join Halliburton as a Data Science Technical Advisor?
- 🚀 Global Impact: Contribute to data-driven transformation in a Fortune 500 company.
- 💡 Innovation-Focused: Work at the intersection of energy, AI, and advanced analytics.
- 📈 Career Growth: Join a forward-thinking, tech-powered environment with room to grow.
- 🌍 Collaborative Culture: Work with cross-functional, global teams on high-visibility projects.
Apply Now
Seize the opportunity to shape the future of data science at Halliburton.
👉 Click here to apply on Halliburton’s Official Careers Page
Grow your career as a Data Science Technical Advisor in Bengaluru and be part of one of the world’s most innovative companies in the energy-tech space.