Technical Professional - Data Science/ Sr. Data Science/ Principal Data Science

Job Duties

• Under general supervision, a Data Scientist will perform data engineering, data modeling or model deployment. A Data Scientist will collaborate to obtain data from sources, complete data clean up and build a data dictionary under guidance.
• This role is able to build models under guidance and understand how to deploy the model and assist in the deployment process.
• An undergraduate degree in STEM and 1+ years of related experience is required, master's degree in STEM preferred.

Role Overview

We are seeking a Senior Data Scientist to join the Innovation Center team in Bengaluru. In this role, you will envision, develop, and deploy next-generation digital and data-driven solutions for the global energy industry, working at the intersection of data science, cloud computing, and applied subsurface domain science.

Key aspects of the role include:

• Working on globally deployed digital products and platforms
• Collaborating with cross-functional, multinational teams
• Solving complex, real-world problems across the oil and gas value chain.

Key Responsibilities

• Design, develop, and deploy advanced analytics, machine learning, deep learning, and generative AI solutions
• Build scalable data products that extract actionable insights from large, complex datasets
• Apply statistical analysis, ML/DL, and GenAI techniques to energy industry workflows (exploration, drilling, completion, production, operations)
• Develop and deploy solutions on iEnergy, Halliburton’s hybrid cloud platform
• Collaborate with domain experts, software engineers, product managers, and researchers
• Communicate insights and recommendations clearly to technical and senior business stakeholders
• Contribute to innovation through patents, publications, and internal/external conference presentations.

Data Science Focus

• Analyze structured and unstructured data to identify patterns, trends, and value opportunities
• Develop end-to-end ML workflows from problem definition to deployment
• Perform rigorous statistical and exploration data analysis
• Translating ambiguous business problems into well-defined analytical tasks
• Demonstrate strong critical thinking, problem-solving, and applied research mindset
• Continuously learn and adopt emerging techniques in machine learning, AI, and generative AI

Knowledge, Skills, and Abilities

Desired Expertise

• Mathematics – Statistics, Multivariate Calculus, Linear Algebra
• Programming Language – Python
• Frameworks –
  • • Data Handling / Visualization – Pandas, NumPy, Seaborn / Matplotlib
    • Machine Learning – Scikit-learn, XGBoost, LightGBM
    • Deep Learning – TensorFlow / PyTorch
    • Generative AI – LangChain, LangGraph, LlamaIndex, etc.
    • REST APIs – Flask / FastAPI
• Generative AI –
  • • Large Language / Vision Models (LLM / LVM): APIs, Hugging Face, fine-tuning
    • Retrieval-Augmented Generation (RAG)
    • Agentic AI – Building sophisticated multi-agent systems
• Version Control – Git (GitHub / GitLab / Bitbucket)
• Databases – SQL
• Preferred Qualitfications
  • • Experience with Cloud Platforms – AWS / Azure (basic to intermediate)
    • Familiarity with Containerization & deployment workflows – Docker
    • Big Data Frameworks – Spark (PySpark)
    • Experience with NoSQL Databases – MongoDB

Qualifications

Education Qualifications

• Masters with 5+ years of experience or Ph.D.
• Degree in Computer Science, Engineering, Earth Sciences, or a closely related field

Candidates having qualifications that exceed the minimum job requirements will receive consideration for higher level roles given (1) their experience, (2) additional job requirements, and/or (3) business needs. Depending on education, experience, and skill level, a variety of job opportunities might be available, including Technical Professional - Data Science, Technical Professional - Sr. Data Science and Technical Professional - Principal Data Science.