Data Scientist – AI, ML

Date Posted: 12/04/2025

Hiring Organization:
Rose International

Position Number: 494217

Industry: Utility

Job Title:

Data Scientist – AI, ML

Job Location:

Houston, TX, USA, 77002

Work Model:
Hybrid

Work Model Details: 4 days onsite,1 day remote

Shift: M-F, 8-5

Employment Type:

Temporary

FT/PT:
Full-Time

Estimated Duration (In months): 7

Min Hourly Rate($): 80.00

Max Hourly Rate($): 86.00

Must Have Skills/Attributes: AI Algorithms, AWS, Data Scientist, GIT, GPT (Generative Pre-trained Transformers), LLM (Large Language Model), Power

BI, Pytorch, Stakeholders

Experience Desired:
Must have Snowflake, SQL, Planantir (or similar data decision operational AI) (3 yrs);
Experience in predictive modeling, NLP, deep learning, and LLM-based applications (e.g., GPT, BERT, (3 yrs);
Proficiency in Python and experience with AI/ML frameworks (e.g., PyTorch, Tensor Flow, Hugging Face) (3 yrs);
Ability to write efficient SQL queries to blend and structure data from multiple sources for modelin (3 yrs);
Experience with AWS (Sage Maker, S3, Redshift), Snowflake, and ML pipeline automation (3 yrs);
Proficiency using Git for code versioning and teamwork (3 yrs);
Dashboarding tools (e.g., Power BI, Dash, Streamlit) for model performance monitoring (3 yrs)

Required Minimum Education:

Bachelor’s Degree

Preferred Education:

Master’s Degree

C2C is not available

Job Description
Education Requirement:
Bachelor’s degree, preferably in Computer Science, Information Technology, Computer Engineering, or related discipline,

Requirements:
AI & Machine Learning:
Experience in predictive modeling, NLP, deep learning, and LLM-based applications (e.g., GPT, BERT, Lang Chain).
Programming:
Proficiency in Python and experience with AI/ML frameworks (e.g., PyTorch, Tensor Flow, 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 (Sage Maker, 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.

Job Summary:

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:
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