Delphi-US
Job Title: Data Scientist - AI/ML Focus (Contract) - Job#5459
Worksite:
Hybrid Onsite mandator Mon-Thur - Houston, TX
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 .
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.
Worksite:
Hybrid Onsite mandator Mon-Thur - Houston, TX
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 .
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.