Aptino, Inc.
Data Scientist
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Scientist with a contract length of "unknown" and a pay rate of "$XX per hour." Key skills include AWS expertise, Python/R programming, and MLOps experience. Industry experience in ML and Data Science is required.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
Unknown
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🗓️ - Date
May 13, 2026
🕒 - Duration
Unknown
-
🏝️ - Location
Unknown
-
📄 - Contract
Unknown
-
🔒 - Security
Unknown
-
📍 - Location detailed
Charlotte, NC
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🧠 - Skills detailed
#Data Cleaning #Python #ML (Machine Learning) #Deployment #Security #AWS Lambda #Data Science #Model Deployment #Forecasting #Lambda (AWS Lambda) #S3 (Amazon Simple Storage Service) #Programming #"ETL (Extract #Transform #Load)" #SageMaker #Compliance #Athena #AWS Glue #Cloud #Redshift #AWS (Amazon Web Services) #Anomaly Detection #Data Security #NLP (Natural Language Processing) #R #Visualization #AI (Artificial Intelligence) #Data Engineering
Role description
Summary – AWS Data Scientist / ML Engineer
Core Responsibilities:
• Design and implement end-to-end Machine Learning pipelines using AWS services:
• Amazon SageMaker
• AWS Glue
• AWS Lambda
• Amazon S3
• Perform:
• Data collection
• Data cleaning
• Feature engineering
• Build predictive models and statistical solutions using:
• Python
• R
• Similar ML/Data Science tools
• Deploy, monitor, and optimize ML models using AWS MLOps best practices
• Collaborate with Data Engineering teams to build and maintain ETL pipelines
• Use AWS analytics tools for reporting and visualization:
• Athena
• Redshift
• QuickSight
• EMR
• Convert business requirements into AI/ML-driven insights and solutions
• Work on AI/ML use cases including:
• Forecasting
• Anomaly Detection
• NLP
• Computer Vision
• Recommendation Systems
• Ensure data security, governance, and compliance standards within AWS environments
Required Skill Set:
• AWS Cloud & ML ecosystem expertise
• Machine Learning & Data Science experience
• Strong Python/R programming
• ETL and Data Engineering understanding
• MLOps & model deployment experience
• Analytical and stakeholder communication skills
Thanks and Regards,
Johnson S – Sr.Technical Recruiter
Aptino, Inc.
8176239800
Johnson.sakare@aptino.com
www.aptino.com
Summary – AWS Data Scientist / ML Engineer
Core Responsibilities:
• Design and implement end-to-end Machine Learning pipelines using AWS services:
• Amazon SageMaker
• AWS Glue
• AWS Lambda
• Amazon S3
• Perform:
• Data collection
• Data cleaning
• Feature engineering
• Build predictive models and statistical solutions using:
• Python
• R
• Similar ML/Data Science tools
• Deploy, monitor, and optimize ML models using AWS MLOps best practices
• Collaborate with Data Engineering teams to build and maintain ETL pipelines
• Use AWS analytics tools for reporting and visualization:
• Athena
• Redshift
• QuickSight
• EMR
• Convert business requirements into AI/ML-driven insights and solutions
• Work on AI/ML use cases including:
• Forecasting
• Anomaly Detection
• NLP
• Computer Vision
• Recommendation Systems
• Ensure data security, governance, and compliance standards within AWS environments
Required Skill Set:
• AWS Cloud & ML ecosystem expertise
• Machine Learning & Data Science experience
• Strong Python/R programming
• ETL and Data Engineering understanding
• MLOps & model deployment experience
• Analytical and stakeholder communication skills
Thanks and Regards,
Johnson S – Sr.Technical Recruiter
Aptino, Inc.
8176239800
Johnson.sakare@aptino.com
www.aptino.com
