Overview
On Site
$DOE
Contract - W2
Contract - Months Contract
Skills
Python
AWS
Snowflake
GPT
BERT
LangChain
Job Details
Job Title: Data Scientist AI/ML
Location: Troy, MI.
Long Term Contract
Only W2. No C2C
Role & 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.
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.
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.
Location: Troy, MI.
Long Term Contract
Only W2. No C2C
Role & 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.
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.
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.
Best Regards:
Ramdeep B
Phone: +1-
Email:
Ramdeep B
Phone: +1-
Email:
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