Senior Data Scientist, Applied AI and Agentic Solutions Engineer

Accountabilities: Model complex business problems and identify meaningful insights using statistical, algorithmic, machine learning, data mining, and visualization techniques. Partner with business and product stakeholders to identify analytical questions, define opportunities, and design experiments that address strategic and operational needs. Conduct advanced statistical analysis on business and experimental data to validate trends, patterns, hypotheses, and potential solutions. Develop predictive models, algorithms, probability engines, and AI-driven capabilities, evaluating their effectiveness against real-world outcomes. Design, develop, test, and deploy generative AI and agentic solutions that support enterprise knowledge discovery, automation, and decision-making. Build Retrieval-Augmented Generation (RAG) solutions, including document ingestion, chunking, embeddings, vector storage, retrieval strategies, prompt engineering, and response generation. Develop software, algorithms, and automated processes to cleanse, integrate, transform, and analyze large datasets from disparate sources. Apply large language models, machine learning, deep learning, semantic search, vector embeddings, and emerging AI technologies to create new data-driven capabilities. Translate business requirements into scalable, secure, maintainable technical solutions across the full lifecycle, from discovery and design through implementation, testing, adoption, and ongoing improvement. Evaluate AI-generated outputs for accuracy, reliability, security, performance, and business value, continuously optimizing models and solutions based on results. Build and maintain production-ready solutions with appropriate monitoring, observability, reliability, scalability, and operational support. Collaborate with analytics, product, user experience, information architecture, and engineering teams to improve dashboards, visualization, experimentation, and data-driven experiences. Communicate complex analytical findings, technical concepts, and recommendations clearly to business leaders, product teams, and other stakeholders. Support enterprise data governance and promote responsible practices around data privacy, security, AI governance, and compliance. Research emerging data science, AI, and software engineering techniques and apply relevant innovations to business challenges. Requirements Bachelor’s degree in computer science, data science, statistics, economics, or a related discipline, or equivalent professional experience. At least 6 years of experience in analytics, data science, machine learning, AI solution development, data and AI engineering, cloud platform engineering, or a related field. Demonstrated experience developing and deploying AI, generative AI, and analytics solutions for enterprise knowledge discovery, automation, or decision support. Experience working across the complete solution lifecycle, including requirements gathering, design, development, testing, implementation, deployment, and user adoption. Strong proficiency in Python and familiarity with modern application technologies such as React, TypeScript, Node.js, APIs, and data visualization frameworks. Hands-on experience with LLMs, machine learning, vector embeddings, semantic search, Snowflake Cortex, or comparable emerging AI technologies. Practical experience designing and deploying RAG architectures, including vector databases, embeddings, retrieval strategies, prompt engineering, and response generation. Strong understanding of AI output evaluation, including accuracy, reliability, security, performance, scalability, and business impact. Experience with AI-assisted development tools and modern engineering practices, with an emphasis on code quality, testing, security, and maintainability. Knowledge of production AI and analytics operations, including monitoring, observability, reliability, scalability, and ongoing support. Understanding of AI security, privacy, governance, responsible AI principles, and relevant compliance considerations. Experience working with cloud-based AI, analytics, and data platforms in enterprise environments. Strong analytical, strategic, and business judgment, with the curiosity to identify new opportunities and shape technical solutions. Excellent written, verbal, presentation, and stakeholder communication skills. Ability to translate complex business needs into practical technology solutions and communicate technical concepts to diverse audiences. Ability to exercise independent judgment, manage changing priorities, and operate effectively in a fast-moving environment. Commitment to staying current with emerging AI techniques, tools, platforms, and development practices. Benefits Base salary range of $84,000–$141,750 , with actual compensation determined by experience and other job-related factors. Potential eligibility for bonuses and commissions as part of the overall compensation package. Remote work opportunity within the United States. Opportunity to work on enterprise-scale AI, data science, analytics, and agentic technology initiatives. Collaborative environment focused on innovation, continuous learning, and cross-functional partnership. Exposure to emerging technologies including generative AI, LLMs, RAG, intelligent agents, semantic search, and advanced analytics. Supportive workplace that values collaboration, inclusion, and diverse perspectives. Opportunities to contribute to solutions with broad organizational and customer impact. Comprehensive benefits are available as part of the overall rewards package, subject to applicable eligibility requirements.