Data Science Consultant
Project Description:
The client is seeking an experienced Data Science Consultant to support a high-impact project within the COO CEDA division. This role involves developing AI-driven analytical models, building data pipelines, and delivering advanced analytics solutions to assist business partners across the organization. The candidate will play a key role in applying machine learning techniques, large language models (LLMs), and natural language processing (NLP) to drive data-driven decision-making.
Responsibilities:
- Develop and optimize data models using Python, PySpark, and machine learning techniques to support AI initiatives.
- Work with Natural Language Processing (NLP), Large Language Models (LLMs), and statistical models like logistic regression and decision trees to deliver advanced analytical solutions.
- Build automated pipelines for model development and collaborate with business teams to translate needs into actionable data models.
- Present findings and insights, ensuring models are scalable and ready for deployment in production environments.
Required Skills:
- 7+ years of experience in Analytics, Data Science, or a related field, with hands-on experience in Python modeling.
- Experience with Large Language Models (LLMs) and Natural Language Processing (NLP).
- Proficiency in Python, SQL, PySpark, and H2O for data modeling and machine learning applications.
- Strong background in statistical modeling, data engineering, logistic regression, and decision tree models.
- Proven ability to organize and analyze large datasets, with a focus on actionable insights.
Preferred Skills:
- Background in automated model development platforms and cloud-based analytics.
- Experience in banking, finance, or regulatory environments (not required, but a plus).
Project Description:
The client is seeking an experienced Data Science Consultant to support a high-impact project within the COO CEDA division. This role involves developing AI-driven analytical models, building data pipelines, and delivering advanced analytics solutions to assist business partners across the organization. The candidate will play a key role in applying machine learning techniques, large language models (LLMs), and natural language processing (NLP) to drive data-driven decision-making.
Responsibilities:
- Develop and optimize data models using Python, PySpark, and machine learning techniques to support AI initiatives.
- Work with Natural Language Processing (NLP), Large Language Models (LLMs), and statistical models like logistic regression and decision trees to deliver advanced analytical solutions.
- Build automated pipelines for model development and collaborate with business teams to translate needs into actionable data models.
- Present findings and insights, ensuring models are scalable and ready for deployment in production environments.
Required Skills:
- 7+ years of experience in Analytics, Data Science, or a related field, with hands-on experience in Python modeling.
- Experience with Large Language Models (LLMs) and Natural Language Processing (NLP).
- Proficiency in Python, SQL, PySpark, and H2O for data modeling and machine learning applications.
- Strong background in statistical modeling, data engineering, logistic regression, and decision tree models.
- Proven ability to organize and analyze large datasets, with a focus on actionable insights.
Preferred Skills:
- Background in automated model development platforms and cloud-based analytics.
- Experience in banking, finance, or regulatory environments (not required, but a plus).