What are the responsibilities and job description for the Principal Data Scientist position at ExecutivePlacements.com?
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
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.
- 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.
- 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.
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- Not specified.