Data Scientist / AI Engineer – Energy & Asset Intelligence

Please apply directly or send your resume to request@tytantech.com with the subject line: “Application – Data Scientist / AI Engineer – Energy & Asset Intelligence”

About the Role

We are seeking a highly skilled Data Scientist / AI Engineer to join our growing AI & Analytics Team within a leading Oil & Gas Private Equity firm. This role is ideal for individuals who combine strong data science and software engineering expertise with a deep understanding of energy markets, operations, or asset optimization. You’ll work closely with our investment, engineering, and technology teams to develop advanced models and data-driven products that enhance decision-making across exploration, production, asset management, and capital allocation.

Key Responsibilities

• Design and implement AI and ML models that support investment analysis, production forecasting, equipment optimization, and market intelligence.
• Build end-to-end data pipelines for data ingestion, transformation, and feature engineering using structured and unstructured datasets (production logs, financial data, IoT, etc.).
• Develop and deploy machine learning solutions (predictive, prescriptive, generative) leveraging modern frameworks (PyTorch, TensorFlow, Scikit-learn, LangChain, etc.).
• Collaborate with engineers, investment analysts, and domain experts to translate business challenges into analytical solutions.
• Work on GenAI and NLP-based applications for unstructured document analysis, deal evaluation, and portfolio reporting.
• Write production-grade, scalable code for ML pipelines and APIs (Python, FastAPI, Flask, etc.).
• Conduct exploratory data analysis (EDA), model validation, and performance tracking using statistical and visualization techniques.
• Contribute to cloud-based ML workflows (Azure, AWS, or GCP), including containerization (Docker) and orchestration (Kubernetes).
• Support internal innovation projects on Agentic AI, MLOps, and generative intelligence for operational insights.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, Petroleum Engineering, Applied Mathematics, or related fields.
• 3–7 years of hands-on experience in data science, AI engineering, or ML operations, preferably in Oil & Gas, Energy, or Financial Services sectors.
• Proven ability to design and implement ML algorithms, time-series models, and optimization techniques.
• Strong programming skills in Python (Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow).
• Experience with data querying and processing tools (SQL, PySpark, Databricks, or Snowflake).
• Knowledge of GenAI/LangChain/OpenAI API for automation or analytical applications.
• Familiarity with cloud platforms (Azure, AWS, or GCP) and CI/CD pipelines for ML deployment.
• Excellent analytical, problem-solving, and communication skills, with the ability to work cross-functionally in technical and investment teams.

Preferred Experience (Nice-to-Have)

• Exposure to energy trading analytics, asset performance modeling, or reservoir data analysis.
• Experience in developing AI copilots or internal chatbots using enterprise data.
• Understanding of financial modeling or risk analysis in private equity or investment environments.
• Experience integrating LLMs or knowledge graphs for document intelligence or portfolio insights.