Senior Data Scientist

POSITION SUMMARY Flexjet is seeking a Senior-Level Enterprise AI Data Scientist to design, develop, and deploy enterprise-scale AI and Generative AI solutions that improve productivity, automate workflows, and enhance decision-making across the organization. This role focuses on building LLM-powered enterprise applications, such as internal knowledge assistants, document processing systems, and workflow automation tools. The ideal candidate has hands-on experience with machine learning, large language models (LLMs), Retrieval-Augmented Generation (RAG), and enterprise data systems. Collaborate with data engineers, software engineers, product teams, and business stakeholders to build secure, scalable, and production-ready AI solutions that align with enterprise governance and compliance standards. DUTIES & RESPONSIBILITIES � Design and implement enterprise-scale machine learning models, including predictive and classification systems � Develop intelligent automation solutions to streamline business workflows � Build and deploy LLM-powered applications, such as enterprise knowledge assistants and chatbots � Design and implement Retrieval-Augmented Generation (RAG) pipelines � Develop solutions for semantic search, document intelligence, and enterprise search capabilities � Optimize prompt engineering workflows and fine-tune models using domain-specific data � Evaluate and benchmark machine learning and LLM model performance � Work with large-scale structured and unstructured data sources across enterprise systems � Design and build scalable data pipelines to support AI and machine learning workflows � Integrate AI solutions with internal systems, APIs, and enterprise platforms � Partner with data engineering teams to design and optimize data architectures � Deploy AI/ML models into production environments � Implement model monitoring, performance tracking, and alerting � Maintain model versioning, reproducibility, and lifecycle management � Support and contribute to CI/CD pipelines for AI and ML deployments � Ensure scalability, reliability, and performance of systems in production environments � Implement responsible AI practices, including fairness, transparency, and risk mitigation � Ensure compliance with enterprise data governance, privacy, and security standards � Support model explainability and documentation requirements � Maintain thorough documentation of models, systems, and workflows � Translate business needs into actionable technical solutions � Work closely with product, engineering, and analytics teams to deliver AI-driven solutions � Communicate technical concepts and solutions clearly to non-technical stakeholders � Contribute to system architecture decisions and design discussions � Document workflows, design decisions, and results EDUCATION & EXPERIENCE � Bachelor's or master's degree in computer science, Information Technology, Data Science, or a related field, or an equivalent combination of education, training, and relevant professional experience. � 5+ years of experience in Data Science, Machine Learning, and AI software engineering, machine learning engineering, platform engineering, MLOps, or DevOps. � Experience building and deploying production ML systems � Hands-on expertise in data preprocessing, feature engineering, and model evaluation � Experience working with APIs, large datasets, and enterprise systems REQUIRED TECHNICAL SKILLS & QUALIFICATIONS � Programming: Strong proficiency in Python and SQL � Experience developing and deploying models (regression, classification, clustering, ensembles, neural networks) � Strong understanding of data preprocessing, feature engineering, and model evaluation � Prompt engineering and optimization � Retrieval-Augmented Generation (RAG) � Embeddings and vector search � Model evaluation and fine-tuning � Experience working with large, complex datasets � Data pipelines, ETL processes, and enterprise data warehouses � API integrations and distributed/enterprise-s…