Job Title: Senior Data Scientist Location: Washington, DC (Hybrid) Type: Contract Position Summary: We are seeking an experienced Senior Data Scientist to lead the development, deployment, and ongoing refinement of innovative machine learning (ML) and artificial intelligence (AI) solutions, including generative AI capabilities. This role will support the entire ML/AI product lifecycle—from identifying use cases to designing models and ensuring ongoing model performance within a cloud-based environment. Key Responsibilities: Development of New Machine Learning and AI Features/Products: Collaborate with cross-functional teams to assess business challenges and identify high-impact opportunities for AI/ML integration. Design, prototype, and implement scalable AI/ML solutions with an iterative and hands-on approach. Evaluate and select suitable models, implement training strategies, and support their transition into production environments. Maintenance and Optimization of Operational AI/ML Systems: Gain deep technical understanding of existing AI/ML implementations, including training data, model pipelines, infrastructure, and monitoring mechanisms. Partner with product owners and architects to define roadmaps, epics, and features for AI/ML systems. Monitor and enhance model accuracy, retrain as necessary by expanding datasets or integrating new features. Uphold high data quality standards to ensure robust model training. Required Qualifications: Minimum of 6 years of hands-on experience in developing, deploying, and maintaining AI/ML solutions in enterprise or academic environments. Bachelor’s degree in Computer Science, Data Science, or a related technical field (Master’s preferred). Advanced programming skills, with expertise in Python and familiarity with other programming languages. Strong background in statistical modeling, data analysis, and machine learning techniques. Experience with Natural Language Processing (NLP), including text normalization, named entity recognition (NER), part-of-speech (POS) tagging, and word embeddings. Proficient with AI/ML frameworks such as Transformers, Scikit-learn, SpaCy, and XGBoost. In-depth understanding of cloud environments, particularly AWS, and deployment of AI/ML solutions in cloud-based infrastructures. Demonstrated ability to work with both technical and non-technical stakeholders. Familiarity with monitoring and improving production-grade models over time.