Data Scientist - W2 Contract

Job Title: Data Scientist Location: Remote Level: Mid to Senior About the Role We’re looking for a data scientist (minimum 5+ years of experience) who is passionate about Natural Language Processing (NLP), Generative AI, and traditional machine learning—and who knows how to ship high-impact, production-grade models. This is a hands-on role where you’ll work across the full ML lifecycle: from prototyping to deployment, with a strong emphasis on production-readiness, APIs, and scalable architecture. You’ll collaborate with AI engineers, product managers, and domain experts to develop intelligent systems that power next-generation insights for the pharma industry. What You’ll Do • Design and develop NLP and generative AI solutions using LLM frameworks like LangChain, LlamaIndex, CrewAI, or direct model provider SDKs/APIs (e.g., OpenAI, Anthropic, HuggingFace). • Build and fine-tune traditional ML models (e.g., classification, regression, clustering) to support data-driven applications. • Create robust and scalable AI pipelines and APIs using Python and FastAPI. • Deploy models to production using AWS services such as ECS, Lambda, and S3, with attention to CI/CD, observability, and cost-effectiveness. • Apply strong system design principles to architect scalable, maintainable, and secure ML systems. • Use critical thinking to analyze complex problems, identify edge cases, and propose pragmatic, data-driven solutions. • Think creatively and outside the box to explore new ML techniques, tools, or approaches that push the boundaries of what we can do. • Work closely with cross-functional teams to turn ambiguous business problems into well-scoped, technically sound AI solutions. • Contribute to a culture of technical excellence and innovation in a fast-moving AI/ML team. Who You Are • Minimum 5 years of industry experience in data science or machine learning. • Strong background in NLP, LLMs, and generative AI—comfortable with both the theory and tooling. • Familiarity with modern LLM stacks such as LangChain, LlamaIndex, CrewAI, or similar. • Skilled in traditional ML methods using libraries like scikit-learn, XGBoost, etc. • Expert-level Python programmer (beyond notebooks)—you write clean, maintainable, testable code. • Experience exposing models as production-ready APIs using FastAPI (or similar frameworks). • Strong understanding of AWS services—especially ECS, Lambda, and S3. • Experience with MLOps and DevOps best practices is a plus (e.g., Docker, Terraform, Azure DevOps, Github Actions). • Proven ability in system architecture, problem-solving, and independently leading projects from concept to deployment. • Comfortable working independently in a fast-paced, collaborative, remote-first environment.