Senior Data Scientist (Generative AI Specialist)

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 an 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 developing and deploying Generative AI models for text, images, and multimodal applications. 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 • 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 • 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 multimodal AI (text + image or text + video models) • 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