Lorven Technologies Inc.
Data Scientist
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Scientist in Charlotte, NC, with a contract length of "unknown" and a pay rate of "unknown." Key skills include Amazon SageMaker, Python, and MLOps. Experience in AWS services and machine learning pipelines is required.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
Unknown
-
🗓️ - Date
July 25, 2026
🕒 - Duration
Unknown
-
🏝️ - Location
On-site
-
📄 - Contract
Unknown
-
🔒 - Security
Unknown
-
📍 - Location detailed
Charlotte, NC
-
🧠 - Skills detailed
#Data Analysis #S3 (Amazon Simple Storage Service) #Amazon EMR (Amazon Elastic MapReduce) #Anomaly Detection #AI (Artificial Intelligence) #Data Governance #Deployment #ML (Machine Learning) #AWS Lambda #Compliance #Code Reviews #IAM (Identity and Access Management) #R #NLP (Natural Language Processing) #Amazon Redshift #PyTorch #Model Deployment #SageMaker #"ETL (Extract #Transform #Load)" #Data Quality #Data Processing #Documentation #Data Engineering #Monitoring #Data Science #Python #AWS Glue #Athena #TensorFlow #Forecasting #Datasets #Security #Visualization #Redshift #Lambda (AWS Lambda) #Scala #Cloud #AWS (Amazon Web Services) #Predictive Modeling #Amazon QuickSight #BI (Business Intelligence)
Role description
Hi-
Our client is looking for a Data Scientist project in Charlotte, NC below is the detailed requirement.
Job Title: Data Scientist
Location: Charlotte, NC
Required Skills: Amazon SageMaker, Python, Machine Learning (ML), AWS Glue, MLOps
Job description:
Design, develop, and implement end-to-end Machine Learning (ML) pipelines on AWS using Amazon SageMaker, AWS Glue, AWS Lambda, and Amazon S3 for scalable data processing, model training, deployment, and monitoring.
Perform data collection, cleansing, preprocessing, transformation, and feature engineering to prepare high-quality structured and unstructured datasets for predictive modeling and advanced analytics.
Build, train, evaluate, fine-tune, and deploy Machine Learning and Statistical Models using Python, R, and ML frameworks such as Scikit-learn, TensorFlow, or PyTorch to solve complex business problems.
Implement MLOps best practices by automating model deployment, versioning, monitoring, retraining, and CI/CD pipelines to ensure reliable, scalable, and production-ready ML solutions.
Collaborate with Data Engineering teams to design, develop, and optimize ETL pipelines, ensuring data quality, availability, governance, and seamless integration across AWS cloud platforms.
Utilize AWS analytics services including Amazon Athena, Amazon Redshift, Amazon EMR, and Amazon QuickSight to perform data analysis, reporting, dashboard development, and business intelligence visualization.
Develop AI/ML solutions for use cases such as forecasting, anomaly detection, Natural Language Processing (NLP), Computer Vision, recommendation systems, and predictive analytics to drive business value.
Partner with business stakeholders, product owners, and cross-functional teams to understand business objectives, translate requirements into data-driven solutions, and communicate actionable insights.
Ensure compliance with AWS security, IAM, encryption, data governance, and cloud best practices while optimizing ML workloads for performance, scalability, reliability, and cost efficiency.
Stay current with emerging AWS AI/ML services, cloud technologies, and industry best practices, contributing to continuous improvement, technical documentation, code reviews, and innovation initiatives.
Hi-
Our client is looking for a Data Scientist project in Charlotte, NC below is the detailed requirement.
Job Title: Data Scientist
Location: Charlotte, NC
Required Skills: Amazon SageMaker, Python, Machine Learning (ML), AWS Glue, MLOps
Job description:
Design, develop, and implement end-to-end Machine Learning (ML) pipelines on AWS using Amazon SageMaker, AWS Glue, AWS Lambda, and Amazon S3 for scalable data processing, model training, deployment, and monitoring.
Perform data collection, cleansing, preprocessing, transformation, and feature engineering to prepare high-quality structured and unstructured datasets for predictive modeling and advanced analytics.
Build, train, evaluate, fine-tune, and deploy Machine Learning and Statistical Models using Python, R, and ML frameworks such as Scikit-learn, TensorFlow, or PyTorch to solve complex business problems.
Implement MLOps best practices by automating model deployment, versioning, monitoring, retraining, and CI/CD pipelines to ensure reliable, scalable, and production-ready ML solutions.
Collaborate with Data Engineering teams to design, develop, and optimize ETL pipelines, ensuring data quality, availability, governance, and seamless integration across AWS cloud platforms.
Utilize AWS analytics services including Amazon Athena, Amazon Redshift, Amazon EMR, and Amazon QuickSight to perform data analysis, reporting, dashboard development, and business intelligence visualization.
Develop AI/ML solutions for use cases such as forecasting, anomaly detection, Natural Language Processing (NLP), Computer Vision, recommendation systems, and predictive analytics to drive business value.
Partner with business stakeholders, product owners, and cross-functional teams to understand business objectives, translate requirements into data-driven solutions, and communicate actionable insights.
Ensure compliance with AWS security, IAM, encryption, data governance, and cloud best practices while optimizing ML workloads for performance, scalability, reliability, and cost efficiency.
Stay current with emerging AWS AI/ML services, cloud technologies, and industry best practices, contributing to continuous improvement, technical documentation, code reviews, and innovation initiatives.
