Data Scientist - AI/ML Focus - OCC

Visa: No H1b,OPT,CPT rest any visa
Location: Worksite: Hybrid Onsite mandator Mon-Thur - Houston, TX
Locals only, PhD or aspiring PhD is highly preferred,Palantir experience will secure an interview
Interview: 1st round video and second 50% possiblity of F2F interview

Key Responsibilities:

• I/ML Model Development: Design, train, and fine-tune machine learning and deep learning models, including LLMs, for predictive analytics, automation, and AI-driven decision-making.
• Data Analysis & Feature Engineering: Collect, process, and analyze structured and unstructured data, engineering relevant features to improve model performance.
• gent-Based & NLP Applications: Develop LLM-based AI solutions with a focus on prompt engineering, fine-tuning, and inference optimization.
• Business Impact & Decision Support: Translate complex data science methodologies into actionable insights, collaborating with stakeholders to drive business value.
• End-to-End Model Deployment: Work with MLOps best practices to deploy and monitor models in production, ensuring scalability, efficiency, and reliability.
• Data Storytelling & Visualization: Develop clear, compelling presentations and dashboards to communicate findings to non-technical stakeholders.

Requirements:
Technical Skills:

• I & Machine Learning: Experience in predictive modeling, NLP, deep learning, and LLM-based applications (e.g., GPT, BERT, LangChain).
• Programming: Proficiency in Python and experience with AI/ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face).
• Data Engineering & SQL: bility to write efficient SQL queries to blend and structure data from multiple sources for modeling and analysis.
• Cloud & MLOps: Experience with AWS (SageMaker, S3, Redshift), Snowflake, and ML pipeline automation.
• Version Control & Collaboration: Proficiency using Git for code versioning and teamwork.

Soft Skills:

• Curious & Innovative: Passionate about solving complex business problems using data and AI.
• Ownership & Initiative: Proactively drive projects from conception to deployment.
• Business Acumen: Understand how AI/ML solutions impact business goals and decision-making.
• Effective Communication: bility to explain technical models and AI methodologies to non-technical audiences.

Preferred Qualifications:

• Graduate degree (Master's or Ph.D.) in a quantitative field (e.g., Computer Science, Data Science, Statistics, Engineering, Mathematics, Economics).
• Experience with dashboarding tools (e.g., Power BI, Dash, Streamlit) for model performance monitoring.
• Familiarity with reinforcement learning and AI agent-based applications .

This role is ideal for a Data Scientist who wants to work at the cutting edge of AI and ML, leveraging LLMs, NLP, and predictive analytics to drive meaningful impact.