Data Scientist

Data ScientistVisa: 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 interviewKey Responsibilities:AI/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.Agent-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:AI & 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: Ability 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: Ability 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.