Freelance Data Science Mentor Jobs in Riverside, CA

Job Summary:
Niagara Bottling is seeking a Principal Data Scientist specializing in Gen AI and Agentic AI to lead R&D initiatives in innovative AI solutions. The role involves strategizing and delivering enterprise-grade AI systems, collaborating with senior leaders, and ensuring the implementation of Responsible AI principles across the organization.
Responsibilities:
• Lead the strategy, design, and delivery of enterprise‑grade GenAI and agentic AI solutions, driving the development of next‑generation agents, LLM‑powered applications, and hybrid GenAI/ML systems that improve decision‑making, automation, and operational efficiency across Niagara’s business units.
• Partner with senior business leaders, product management, and cross‑functional technology teams to translate ambiguous or complex business challenges into clear problem statements, measurable outcomes, and prioritized AI initiatives.
• Architect robust agentic systems, including multi‑step orchestration, tool‑use agents, retrieval‑augmented workflows, grounding layers, and guardrail frameworks that ensure reliability, safety, and domain accuracy.
• Design and implement scalable analytic and modeling approaches, including feature engineering, embedding strategies, retrieval pipelines, fine‑tuning, prompt engineering, supervised learning, and hybrid architectures combining classical ML with GenAI capabilities.
• Develop, prototype, and operationalize LLM‑driven solutions using enterprise platforms such as Azure OpenAI, Databricks, Snowflake Cortex, Oracle AI Agent Studio, and containerized microservices.
• Build reusable, interpretable, and production‑ready models, agents, and pipelines, ensuring they meet standards for scalability, observability, resilience, and maintainability.
• Establish and own Niagara’s LLMOps and agent lifecycle practices, including CI/CD for models and agents, monitoring, evaluation frameworks, prompt testing, drift detection, and continuous improvement workflows.
• Champion Responsible AI principles, embedding safety, fairness, explainability, privacy, security, grounding, and governance throughout the agent and model development lifecycle.
• Define technical standards and best practices for GenAI development, including vector database usage, evaluation frameworks, embeddings, data preparation workflows, and content grounding strategies.
• Collaborate with IT, data engineering, and platform teams to ensure required infrastructure—data access, compute environments, vector stores, APIs, and application integration layers—is in place for scalable deployment.
• Influence executive stakeholders by crafting compelling narratives, visualizations, and recommendations that communicate complex AI concepts in business‑relevant terms and drive strategic alignment.
• Coach, mentor, and uplift the technical capabilities of data scientists and senior individual contributors, providing thought leadership, code reviews, architectural guidance, and development plans.
• Drive innovation initiatives and proofs‑of‑concept, evaluating emerging GenAI frameworks, agent orchestration tools, evaluation stacks, retrieval technologies, and model families.
• Contribute to enterprise AI governance, including model/agent documentation, risk assessments, access control, versioning, testing standards, and audit readiness.
• Foster cross‑functional collaboration, identifying opportunities to leverage GenAI across manufacturing, supply chain, commercial operations, HR, legal, and corporate functions.
• Represent DDI as a subject‑matter expert for GenAI and agentic AI, sharing insights, educating stakeholders, and building organizational readiness for advanced AI capabilities.
• Analytics Product Expertise Strong knowledge of agile analytics product delivery, full-stack development (Data Engineering, Data Science, UX/UI), and industry best practices.
• Product & Project Management Skilled in developing Product Briefs, managing roadmaps, backlog prioritization, release planning, sprint metrics, and cross-team coordination while ensuring business value-driven outcomes.
• Business & Process Understanding deep comprehension of business processes, functional digital capabilities (Supply Chain, Manufacturing, Finance, Sales & Marketing), and high-quality analytics delivery.
• Change & People Management skilled in managing change initiatives, fostering collaboration, and balancing competing priorities in a fast-paced environment.
Qualifications:
Required:
• 10+ years of experience in Data Science or Analytics, including 4+ years leading projects or technical teams.
• Deep expertise in Machine Learning, Generative AI, Large Language Models (LLMs), Retrieval‑Augmented Generation (RAG), and agentic AI systems.
• Demonstrated experience designing and delivering production AI systems using Azure and Databricks.
• Strong storytelling, executive communication, and influence skills, with an ability to translate complex AI concepts into business outcomes.
• Bachelor's Degree in Computer Science/Data Science/Statistics or other related field.
Preferred:
• 12–15+ years of experience in Data Science, AI/ML engineering, or advanced analytics, including leading platform‑level or enterprise GenAI programs.
• Experience working with agent orchestration frameworks, vector databases, evaluation stacks, and modern LLMOps tooling.
• Experience with Oracle AI Agent Studio.
• Master’s Degree in Computer Science/Data Science/Statistics or other related field.
• Agentic AI / Gen AI / Machine Learning or Advanced Analytics certifications.
Company:
Niagara Bottling provides bottled water and bottled sports drinks. Founded in 1963, the company is headquartered in Philadelphia, USA, with a team of 5001-10000 employees. The company is currently Late Stage.