Data Scientist/ AI/ML

Job Description -

Job Title: Data Scientist AI/ML Focus
Worksite: Hybrid Onsite mandator Mon-Thur Houston, TX
6 Months
Must have Linkedin

Need Ph.D. Candidates

Overview:
We are seeking a curious, proactive, and innovative Data Scientist with a strong foundation in AI/ML and Large Language Models (LLMs) to join our team. The ideal candidate has experience blending various datasets, building statistical/machine learning models, and deploying AI-driven solutions that drive business impact.
This role involves working with LLMs, natural language processing (NLP), and deep learning techniques to develop AI-powered applications. You will play a pivotal role in designing, training, and deploying scalable AI/ML models, while also translating complex data insights into actionable business strategies.Key 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.