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.