

Senior Data Scientist
β - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior Data Scientist with a contract length of "unknown" and a pay rate of "unknown." It requires advanced machine learning skills, experience with LLMs, strong programming in Python and SQL, and proficiency in Azure Data Platform.
π - Country
United States
π± - Currency
$ USD
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π° - Day rate
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ποΈ - Date discovered
July 24, 2025
π - Project duration
Unknown
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ποΈ - Location type
Remote
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π - Contract type
Unknown
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π - Security clearance
Unknown
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π - Location detailed
United States
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π§ - Skills detailed
#Data Lake #Model Evaluation #Data Science #Azure Data Factory #ML (Machine Learning) #Data Engineering #Code Reviews #Azure Machine Learning #Programming #Data Wrangling #Synapse #Azure Synapse Analytics #Python #Spark (Apache Spark) #Data Transformations #Azure #Storage #SQL (Structured Query Language) #"ETL (Extract #Transform #Load)" #Data Processing #Data Pipeline #ADF (Azure Data Factory)
Role description
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Senior Level Data ScientistβRemote with very rare travel needed
Core Technical Expertise
1. Advanced Machine Learning Skills
1. Deep understanding of modeling, feature engineering, model evaluation, and tuning β with applied experience using Scikit-learn, or similar. Experience deploying ML models in production.
1. Experience with Large Language Models (LLMs)
1. Familiar with prompt engineering, fine-tuning, or integrating LLMs into data workflows. Understands when LLMs are appropriate and how to evaluate their output critically.
1. Strong Programming Skills (Python & SQL)
1. Writes clean, efficient, and modular code. Skilled in working with structured and unstructured data.
1. Experience with Spark on Azure Synapse
1. Able to work with distributed data processing in Spark via Azure Synapse Analytics β including handling large-scale data transformation and optimization.
1. Azure Data Platform Proficiency
1. Comfortable working in Azure Data Lake, Azure Machine Learning, Blob Storage, and deploying models through Azure tools.
Problem Solving & Data Product Thinking
1. End-to-End Data Science Ownership
1. Able to independently take a problem from data wrangling through model development to delivery and impact measurement.
1. Data Engineering Competence
1. Understands and can help build or improve data pipelines, source clean data, and manage data transformations using tools like Spark or Azure Data Factory.
1. Applied, Outcome-Oriented Mindset
1. Prioritizes solving the right problems β and making measurable impact, especially in clinical or healthcare contexts.
Mentorship & Knowledge Sharing
1. Teaches Others Through Pair Programming & Walkthroughs
1. Patient and confident helping others learn data science, whether through code reviews, informal pair sessions, or concept explanations.
1. Translates Complexity into Clarity
1. Can articulate technical concepts for non-technical stakeholders and junior teammates alike β especially important in cross-functional healthcare settings.
1. Supportive & Approachable
1. Creates an environment where others feel safe asking questions and growing.
Collaboration & Soft Skills
1. Cross-Functional Communicator
1. Comfortable collaborating with clinicians, analysts, and operational staff to shape usable solutions.
1. Team-First Attitude
1. Seeks shared success, not just personal wins. Contributes to building team culture and trust.
1. Adaptable & Humble
1. Welcomes feedback, adjusts based on new insights, and knows when to take the lead or follow.
1. Proactive and Self-Directed
1. Spots inefficiencies, builds internal tools, or creates learning opportunities for others without waiting to be asked.