Technical Professional - Data Science/Senior Technical (AI Engineer)
Summary
Build and deploy AI/ML models (NLP, deep learning) to improve energy-industry processes, migrating legacy SQL reports to a Snowflake data lake using Python and ML frameworks.
- 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.
- Transition legacy SQL Server reporting infrastructure to a Snowflake-based data lake architecture
- Understand business requirements, analyze operational challenges, and develop AI-driven solutions that deliver measurable business value and process improvements
- Design, develop, and implement AI/ML models and algorithms
- Build and deploy machine learning, deep learning, and NLP solutions
- Work with structured and unstructured datasets to extract meaningful insights
- Develop and optimize data pipelines for model training and deployment
- Integrate AI models into applications through APIs or cloud platforms
- Monitor model performance and continuously improve model accuracy and efficiency
- Stay updated with the latest advancements in AI and machine learning technologies
- An undergraduate degree in STEM and 1+ years of related experience is required, master's degree in STEM preferred.
- AI / Machine Learning certifications
- Data Analyst certifications
- Data Science certifications
- Cloud certifications (Azure, AWS, or GCP)
- Strong programming skills in Python (preferred), Java, or C++
- Experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn
- Hands-on experience with Snowflake data platform