Data Scientist
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Scientist with a 6-month contract, offering a pay rate of "competitive salary." The position requires 5+ years of Data Science experience, 2–3 years in AI/ML, and mandatory AWS expertise.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
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🗓️ - Date discovered
September 25, 2025
🕒 - Project duration
Unknown
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🏝️ - Location type
Unknown
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📄 - Contract type
Unknown
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🔒 - Security clearance
Unknown
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📍 - Location detailed
Dallas-Fort Worth Metroplex
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🧠 - Skills detailed
#Data Science #AWS Glue #NoSQL #TensorFlow #SageMaker #PyTorch #AWS (Amazon Web Services) #Deep Learning #"ETL (Extract #Transform #Load)" #Transformers #Azure #SQL (Structured Query Language) #NLP (Natural Language Processing) #Scala #Big Data #AI (Artificial Intelligence) #ML (Machine Learning) #Jupyter #A/B Testing #Cloud #Datasets #Docker #GCP (Google Cloud Platform) #GIT #Python
Role description
Responsibilities
• Lead data science projects, delivering actionable insights that support business decisions.
• Build and deploy AI/ML models with a focus on scalability and performance.
• Work with large datasets to extract patterns, trends, and customer behavior insights.
• Apply advanced ML concepts (e.g., Deep Learning, GANs, Transformers, NLP, LLMs).
• Design and optimize ELT/ETL processes using AWS Glue and related services.
• Conduct data segmentation, churn analysis, market basket modeling, and A/B testing.
• Collaborate with stakeholders to define requirements, walk through use cases, and deliver measurable outcomes.
Required Skills & Qualifications
• 5+ years of experience in Data Science.
• 2–3 years of hands-on AI/ML development.
• Strong proficiency in Python and SQL.
• Mandatory AWS expertise (Azure/GCP not acceptable).
• Experience with CI/CD and MLOps (Git, Docker).
• Familiarity with distributed datastores (SQL, NoSQL) and big data tools.
• Experience with Cloud Llama or similar LLM frameworks.
Nice to Have
• Experience with TensorFlow, PyTorch, Jupyter Notebooks, SageMaker.
• Experience working with large-scale industry datasets.
• Hands-on with model management frameworks and modern LLMs (Claude, Llama, Haiku, Gemma).
Soft Skills
• Strategic thinker with strong analytical and problem-solving skills.
• Ability to clearly explain use cases and insights to business and technical teams.
• Strong communication skills, with experience influencing customer acquisition and retention strategies.
Responsibilities
• Lead data science projects, delivering actionable insights that support business decisions.
• Build and deploy AI/ML models with a focus on scalability and performance.
• Work with large datasets to extract patterns, trends, and customer behavior insights.
• Apply advanced ML concepts (e.g., Deep Learning, GANs, Transformers, NLP, LLMs).
• Design and optimize ELT/ETL processes using AWS Glue and related services.
• Conduct data segmentation, churn analysis, market basket modeling, and A/B testing.
• Collaborate with stakeholders to define requirements, walk through use cases, and deliver measurable outcomes.
Required Skills & Qualifications
• 5+ years of experience in Data Science.
• 2–3 years of hands-on AI/ML development.
• Strong proficiency in Python and SQL.
• Mandatory AWS expertise (Azure/GCP not acceptable).
• Experience with CI/CD and MLOps (Git, Docker).
• Familiarity with distributed datastores (SQL, NoSQL) and big data tools.
• Experience with Cloud Llama or similar LLM frameworks.
Nice to Have
• Experience with TensorFlow, PyTorch, Jupyter Notebooks, SageMaker.
• Experience working with large-scale industry datasets.
• Hands-on with model management frameworks and modern LLMs (Claude, Llama, Haiku, Gemma).
Soft Skills
• Strategic thinker with strong analytical and problem-solving skills.
• Ability to clearly explain use cases and insights to business and technical teams.
• Strong communication skills, with experience influencing customer acquisition and retention strategies.
