Yorkshire Global Solutions Inc.
Senior Data Scientist
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior Data Scientist with 10+ years of experience, offering a remote W2 contract. Key skills include Python, SQL, Machine Learning, and cloud platforms (AWS/Azure/GCP). Candidates must have expertise in TensorFlow/PyTorch and data pipeline development.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
Unknown
-
🗓️ - Date
July 17, 2026
🕒 - Duration
Unknown
-
🏝️ - Location
Remote
-
📄 - Contract
W2 Contractor
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🔒 - Security
Unknown
-
📍 - Location detailed
United States
-
🧠 - Skills detailed
#GCP (Google Cloud Platform) #Distributed Computing #ML (Machine Learning) #"ETL (Extract #Transform #Load)" #Spark (Apache Spark) #Agile #GIT #AWS (Amazon Web Services) #Classification #Data Pipeline #Docker #Data Engineering #Data Science #Data Extraction #PyTorch #Azure #Deep Learning #Datasets #Regression #Python #Scrum #Pandas #TensorFlow #NumPy #MLflow #Cloud #Forecasting #Visualization #Data Architecture #SQL (Structured Query Language) #Databricks #Scala
Role description
Hi,
This is Prashant, a Lead Recruiter from Yorkshire Global Solutions Inc.
We are currently hiring for the below role.
Note :: This is a W2 role only :: Please Do not Apply - 1099/C2C Candidate
Visa Accepted - USC, GC, H4 EAD, L2 EAD, H1B- Transfer (Not considering H1B)
Once you applied Ping Me with your Visa Status -
https://www.linkedin.com/in/usaprashantrathore/
Job Title: Senior Data Scientist (W2 Candidates Only)
Location: USA Remote
Minimum Exp: 10+ Years
Must-Have Technologies:
Python, SQL, Machine Learning, Deep Learning, TensorFlow/PyTorch, Scikit-learn, Pandas, NumPy, Spark, Databricks, AWS/Azure/GCP, MLflow, Git, Docker
Job Description:
• Design, develop, and deploy scalable machine learning and predictive analytics solutions to solve complex business problems.
• Build, train, validate, and optimize machine learning and deep learning models using Python, Scikit-learn, TensorFlow, or PyTorch.
• Perform data extraction, cleansing, transformation, and feature engineering on large structured and unstructured datasets.
• Develop statistical models, forecasting solutions, recommendation engines, and classification or regression models to support business initiatives.
• Create robust data pipelines using Spark, Databricks, or distributed computing frameworks for processing high-volume datasets.
• Analyze large datasets using SQL, Pandas, and NumPy to identify trends, patterns, and actionable business insights.
• Deploy machine learning models into production environments using Docker, MLflow, cloud-native services, and MLOps best practices.
• Collaborate with Data Engineers to build scalable data architectures and integrate machine learning solutions with enterprise applications.
• Monitor model performance, retrain models when necessary, improve prediction accuracy, and ensure model reliability through continuous evaluation.
• Present analytical findings and business recommendations through dashboards, visualizations, and reports while working closely with cross-functional teams in Agile/Scrum environments.
Hi,
This is Prashant, a Lead Recruiter from Yorkshire Global Solutions Inc.
We are currently hiring for the below role.
Note :: This is a W2 role only :: Please Do not Apply - 1099/C2C Candidate
Visa Accepted - USC, GC, H4 EAD, L2 EAD, H1B- Transfer (Not considering H1B)
Once you applied Ping Me with your Visa Status -
https://www.linkedin.com/in/usaprashantrathore/
Job Title: Senior Data Scientist (W2 Candidates Only)
Location: USA Remote
Minimum Exp: 10+ Years
Must-Have Technologies:
Python, SQL, Machine Learning, Deep Learning, TensorFlow/PyTorch, Scikit-learn, Pandas, NumPy, Spark, Databricks, AWS/Azure/GCP, MLflow, Git, Docker
Job Description:
• Design, develop, and deploy scalable machine learning and predictive analytics solutions to solve complex business problems.
• Build, train, validate, and optimize machine learning and deep learning models using Python, Scikit-learn, TensorFlow, or PyTorch.
• Perform data extraction, cleansing, transformation, and feature engineering on large structured and unstructured datasets.
• Develop statistical models, forecasting solutions, recommendation engines, and classification or regression models to support business initiatives.
• Create robust data pipelines using Spark, Databricks, or distributed computing frameworks for processing high-volume datasets.
• Analyze large datasets using SQL, Pandas, and NumPy to identify trends, patterns, and actionable business insights.
• Deploy machine learning models into production environments using Docker, MLflow, cloud-native services, and MLOps best practices.
• Collaborate with Data Engineers to build scalable data architectures and integrate machine learning solutions with enterprise applications.
• Monitor model performance, retrain models when necessary, improve prediction accuracy, and ensure model reliability through continuous evaluation.
• Present analytical findings and business recommendations through dashboards, visualizations, and reports while working closely with cross-functional teams in Agile/Scrum environments.
