Data Scientist / AI Engineer – Energy & Asset Intelligence

request@tytantech.com

About the Role

Data Scientist / AI Engineer

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.