Principal Data Scientist

Job Summary

The Principal Data Scientist role focuses on developing and deploying AI/ML solutions, particularly using Large Language Models, to drive business insights. The role involves hands-on work with data platforms, advanced modeling techniques, and collaboration with stakeholders to translate data into actionable strategies.

Location:Houston, Texas, United States

Responsibilities

• Design, train, validate, and optimize machine learning, deep learning, and LLM-based models.
• Collect, cleanse, and analyze structured and unstructured datasets, creating high-quality features.
• Build and fine-tune LLM-powered applications, including prompt engineering and advanced NLP pipelines.
• Partner with business teams to convert statistical outputs into actionable insights.
• Implement production-ready ML pipelines using MLOps best practices.
• Create dashboards, visualizations, and executive-level deliverables to communicate insights.
• Collaborate with engineering, product, and analytics teams to deliver integrated AI/ML solutions.
  
  

Required Skills & Certifications

• Strong experience with Snowflake, SQL, and decision intelligence / operational AI systems.
• Expertise in AI, machine learning, NLP, deep learning, and LLMs (GPT, BERT, LangChain, etc.).
• Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, Hugging Face.
• Strong data engineering experience with data blending, transformation, and modeling.
• Cloud experience in AWS (SageMaker, S3, Redshift) and ML automation.
• Skilled in version control tools such as Git.
• Highly curious, innovative, and proactive problem-solver.
• Strong ownership mindset; ability to drive projects from concept to deployment independently.
• Excellent communication skills with the ability to articulate technical concepts to non-technical teams.
• Strong business acumen and a strategic approach to applying AI/ML in real-world scenarios.
  
  

Preferred Skills & Certifications

• Master's or Ph.D. in Computer Science, Data Science, Engineering, Statistics, Mathematics, Economics, or a related quantitative field.
• Experience with dashboarding tools such as Power BI, Dash, Streamlit, or similar.
• Familiarity with reinforcement learning, AI agents, and next-generation intelligent systems.
  
  

Special Considerations

• Not specified.
  
  

Scheduling

• Not specified.