Data Scientist

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Scientist III, remote for 6 months, offering a pay rate of "unknown." Requires a PhD or Master's with 5+ years, proficiency in Python, PyTorch, TensorFlow, and experience with AI/ML solutions and Bayesian modeling.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
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🗓️ - Date discovered
May 22, 2025
🕒 - Project duration
More than 6 months
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🏝️ - Location type
Remote
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📄 - Contract type
Unknown
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🔒 - Security clearance
Unknown
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📍 - Location detailed
United States
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🧠 - Skills detailed
#PyTorch #Data Analysis #Python #ML (Machine Learning) #TensorFlow #Computer Science #Data Science #Deep Learning #AI (Artificial Intelligence) #Cloud #Datasets #GCP (Google Cloud Platform) #BERT #AWS (Amazon Web Services) #Azure
Role description
Job Title: Data Scientist III Location: Remote Duration: 6 Months Key Responsibilities · Collaborate with cross-functional teams to design, develop, and implement AI models tailored to business needs. · Integrate and adapt external AI programs, ensuring compatibility with internal systems. · Develop and refine deep learning models using Python, PyTorch, TensorFlow, and related tools. · Research and implement large language models (LLMs), contributing to their application in Real World Data analysis. · Apply Bayesian modeling techniques for multimodal data analysis. · Support ongoing model troubleshooting, optimization, and performance improvement. Qualifications Education: · PhD in Computational Science, Computer Science, Data Science, or a related field (recent graduates welcome), or · Master’s degree with 5+ years of relevant experience (PhD preferred). Technical Skills: · Proficiency in Python with hands-on experience in PyTorch or TensorFlow. · Applied experience in deploying AI/ML solutions involving large language models. · Familiarity with Bayesian modeling in AI contexts (preferred). Soft Skills: · Strong analytical thinking and problem-solving abilities. Preferred Skills · Experience applying AI methodologies in biological research or on biological datasets. · Hands-on experience in image analysis using deep learning techniques. · Familiarity with cloud computing environments (e.g., AWS, GCP, Azure). · Exposure to additional AI frameworks or models such as BERT, LLAMA, etc.