Jade Business Services (JBS)
Jr Data Scientist
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Jr Data Scientist with a 6-month W2 contract, offering a pay rate of "$XX/hour." Candidates must have 3 years of machine learning experience in the healthcare domain, strong Python and SQL skills, and familiarity with Databricks and cloud platforms.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
May 30, 2026
🕒 - Duration
Unknown
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🏝️ - Location
Unknown
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📄 - Contract
W2 Contractor
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🔒 - Security
Unknown
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📍 - Location detailed
United States
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🧠 - Skills detailed
#Clustering #Model Deployment #MLflow #Python #AWS (Amazon Web Services) #Data Processing #ML (Machine Learning) #Databricks #Classification #Data Science #Pandas #Monitoring #Regression #Scala #Cloud #Forecasting #Data Engineering #SQL (Structured Query Language) #Big Data #Apache Spark #PySpark #Model Evaluation #Deployment #Spark (Apache Spark) #Datasets #Azure #GCP (Google Cloud Platform) #Distributed Computing
Role description
NOTE: Only W2
Key Responsibilities:
• Develop and deploy classic machine learning models, including regression, classification, clustering, and time-series forecasting.
• Utilize Databricks for data processing, feature engineering, and model training.
• Work with large-scale datasets from structured and unstructured sources.
• Optimize model performance and scalability within a cloud-based environment.
• Collaborate with data engineers and business stakeholders to translate data insights into actionable business solutions.
• Implement MLOps best practices for model deployment and monitoring.
Required Skills & Experience:
• Minimum of 3 years of experience in machine learning and data science.
• Need Experience in Healthcare Domain.
• Strong proficiency in Python (Pandas, Scikit-learn, MLflow, PySpark) and SQL.
• Hands-on experience with Databricks and Apache Spark.
• Solid understanding of feature engineering, model evaluation, and hyperparameter tuning.
• Experience working with cloud platforms such as Azure, AWS, or GCP.
• Strong problem-solving and analytical skills with a business-driven mindset.
Preferred Qualifications:
• Experience with time-series forecasting and predictive analytics.
• Knowledge of distributed computing and big data processing.
• Familiarity with ML lifecycle management using MLflow.
• Think critically about analyses to ensure the conclusions make sense before sharing
NOTE: Only W2
Key Responsibilities:
• Develop and deploy classic machine learning models, including regression, classification, clustering, and time-series forecasting.
• Utilize Databricks for data processing, feature engineering, and model training.
• Work with large-scale datasets from structured and unstructured sources.
• Optimize model performance and scalability within a cloud-based environment.
• Collaborate with data engineers and business stakeholders to translate data insights into actionable business solutions.
• Implement MLOps best practices for model deployment and monitoring.
Required Skills & Experience:
• Minimum of 3 years of experience in machine learning and data science.
• Need Experience in Healthcare Domain.
• Strong proficiency in Python (Pandas, Scikit-learn, MLflow, PySpark) and SQL.
• Hands-on experience with Databricks and Apache Spark.
• Solid understanding of feature engineering, model evaluation, and hyperparameter tuning.
• Experience working with cloud platforms such as Azure, AWS, or GCP.
• Strong problem-solving and analytical skills with a business-driven mindset.
Preferred Qualifications:
• Experience with time-series forecasting and predictive analytics.
• Knowledge of distributed computing and big data processing.
• Familiarity with ML lifecycle management using MLflow.
• Think critically about analyses to ensure the conclusions make sense before sharing
