Global Business Ser. 4u
Data Scientist
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Scientist with strong experience in Databricks and Snowflake, focusing on real-time ML workflows, recommendation engines, and MLOps. Remote work is available; expertise in cloud-based big data ecosystems is required.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
May 8, 2026
🕒 - Duration
Unknown
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🏝️ - Location
Remote
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
United States
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🧠 - Skills detailed
#Distributed Computing #Data Processing #Model Optimization #Scala #Data Science #Databricks #Big Data #Snowflake #Cloud #ML (Machine Learning)
Role description
Local to FL preferred Open to Remote
Contract
Job Description
• Strong experience with Databricks for real-time machine learning workflows, streaming, and large-scale data processing.
• Hands-on expertise in Snowflake including data platform management and feature store implementation.
• Design, build, and optimize recommendation engines for personalized customer experiences.
• Experience deploying and managing real-time inference pipelines and production-grade ML systems.
• Strong understanding of machine learning lifecycle, model optimization, and MLOps practices.
• Ability to design scalable, high-performance data and ML architectures.
• Solid foundation in Data Science, statistical modeling, and predictive analytics.
• Experience working with cloud-based big data ecosystems and distributed computing frameworks.
• Strong collaboration and problem-solving skills with the ability to work across engineering and analytics teams.
Local to FL preferred Open to Remote
Contract
Job Description
• Strong experience with Databricks for real-time machine learning workflows, streaming, and large-scale data processing.
• Hands-on expertise in Snowflake including data platform management and feature store implementation.
• Design, build, and optimize recommendation engines for personalized customer experiences.
• Experience deploying and managing real-time inference pipelines and production-grade ML systems.
• Strong understanding of machine learning lifecycle, model optimization, and MLOps practices.
• Ability to design scalable, high-performance data and ML architectures.
• Solid foundation in Data Science, statistical modeling, and predictive analytics.
• Experience working with cloud-based big data ecosystems and distributed computing frameworks.
• Strong collaboration and problem-solving skills with the ability to work across engineering and analytics teams.
