Data Scientist- AI/ML , NLP focus

Overview

Hybrid
$80 - $90
Contract - Independent
Contract - W2
Contract - 12 Month(s)

Skills

Amazon Redshift
Amazon S3
Amazon SageMaker
Artificial Intelligence
BERT
Business Acumen
Cloud Computing
Collaboration
Computer Science
Dash Python
Dashboard
Data Analysis
Data Engineering
Data Science
Decision Support
Decision-making
Deep Learning
Economics
Effective Communication
FOCUS
Git
LangChain
Large Language Models (LLMs)
Machine Learning (ML)
Machine Learning Operations (ML Ops)
Mathematics
Microsoft Power BI
Modeling
Natural Language Processing
Optimization
Performance Monitoring
Predictive Analytics
Predictive Modelling
Presentations
Prompt Engineering
PyTorch
Python
SQL
Scalability
Snow Flake Schema
Statistics
Teamwork
TensorFlow
Unstructured Data
Version Control
Visualization

Job Details

At SACRUM Technologies, what we do here changes your WORLD! Come, let us make it happen! You won't go wrong- We only believe in building great teams TOGETHER to deliver great results!

Job Title: Data Engineering/Scientist AI/ML Focus

Worksite: Onsite , Mon-Thurs Houston, TX

Must Have: Snowflake, SQL, Palantir (or similar data decision Operational AI)

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.

 

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:

 

  • 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.
  • 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.
  • 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).

 

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