Senior Data Scientist - Generative AI Model Development

Looking for a contractor to fill a role with a major US retail healthcare provider. 60% of our past placed contractors have led to full time employment positions on the internal data science team.

High hourly rate!! Fully Remote! 40 hours a week, 9am-5pm EST. This is a non C2C position.

We’re seeking a highly skilled and experienced Senior Data Scientist on a contract basis. This role will focus on creating ML forecast models using social media as main source of data. You’ll collaborate with cross-functional teams to build creative AI systems that generate high-quality outputs and accelerate innovation.

Key Responsibilities

• Design, build, and fine-tune generative AI models (text, image, or multimodal)
• Develop data pipelines for large-scale training and evaluation of generative systems
• Apply deep learning techniques (transformers, diffusion models, GANs) to generate synthetic content

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• Optimize models for efficiency, quality, and safe deployment
• Collaborate with engineering teams to integrate generative AI into production products
• Conduct exploratory data analysis and communicate findings to stakeholders

Required Skills & Qualifications

• 3+ years of experience in data science or machine learning roles
• Strong proficiency in Python and libraries such as NumPy, Pandas, Scikit-learn, TensorFlow, or PyTorch
• Hands-on experience with generative models (e.g., GPT, Stable Diffusion, DALL·E, MidJourney, or custom architectures)
• Proven expertise in fine-tuning or deploying generative AI applications in production

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• Familiarity with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes)
• Experience with evaluating generative model outputs for quality and bias
• Excellent problem-solving skills and ability to work independently

Preferred Qualifications

• Experience with models trained with side social media data.
• Knowledge of advanced generative techniques such as control nets, prompt tuning, or diffusion pipelines
• Familiarity with MLOps tools and practices for generative AI
• Background in AI research or generative modeling