

Data Scientist
β - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Scientist with 12+ years of experience, located in Dallas & Charlotte, offering a competitive pay rate. Key skills include AI/ML, NLP, Azure/Open AI, Python/R/SAS/SQL, and project management. Certifications preferred.
π - Country
United States
π± - Currency
$ USD
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π° - Day rate
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ποΈ - Date discovered
June 18, 2025
π - Project duration
Unknown
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ποΈ - Location type
Unknown
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π - Contract type
Unknown
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π - Security clearance
Unknown
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π - Location detailed
Dallas, TX
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π§ - Skills detailed
#Scala #Statistics #Cloud #Automation #Data Extraction #Azure #Visualization #AI (Artificial Intelligence) #R #ML (Machine Learning) #Storage #Data Mining #Data Ingestion #SQL (Structured Query Language) #Data Cleaning #AWS (Amazon Web Services) #Data Science #"ETL (Extract #Transform #Load)" #Monitoring #Predictive Modeling #Data Pipeline #Data Processing #Azure Machine Learning #Data Architecture #SageMaker #Python #Datasets #SAS #NLP (Natural Language Processing) #Project Management
Role description
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Role: Data Scientist
Location: Dallas & Charlotte
Exp: 12+yrs
Responsibilities:
β’ Strong analytic skills with the ability to extract, collect, organize, analyze and interpret trends or patterns in complex data sets
β’ Experience in AI / ML with NLP
β’ Experience in building Gen AI solutions on Azure / Open AI
β’ Azure Document Intelligence is preferred but not mandatory
β’ Experience in analytics, advanced analytics/statistics, predictive modeling, machine learning, data visualization
β’ Understanding of machine learning techniques and algorithms
β’ Experience in python/R/SAS/SQL for data extraction, data mining, and predictive analytics
β’ Demonstrated project management skills
β’ Effective interpersonal, verbal and written communication skills
β’ Certifications in relevant fields is preferred, but it is not mandatory
Key Responsibilities:
β’ AI/ML Model Development: Utilize available models to design, train, and deploy machine learning models. Leverage Cloud / On premise / Hybrid environments platforms like Amazon SageMaker and Azure Machine Learning for end-to-end machine learning lifecycle management.
β’ Data Architecture Design: Architect and manage robust scalable data infrastructures supporting AI/ML project requirements including data ingestion, storage, and processing workflows.
β’ Data Processing: Conduct data cleaning, preprocessing, and analysis, preparing datasets for model training for effective data handling and insights generation.
β’ Automation Services Integration: Automate data pipelines and integrate AI/ML models into production systems. Enhance business processes and decision-making capabilities through cloud-based AI solutions.
β’ Performance Monitoring: Monitor the performance of AI models and the efficiency of data pipelines across cloud platforms, adjusting resources and configurations to ensure optimal operation.
β’ Cross-Functional Collaboration: Collaborate with enterprise architects, data scientists, and business stakeholders to identify and exploit AI-driven automation opportunities on AWS, Azure.
Regards
Praveen Kumar R
Talent Acquisition Group β Strategic Recruitment Manager
praveen.r@themesoft.com