Minimum Qualifications: 8+ years in Data Science/ML.
Experience in CPG/retail growth, demand forecasting, pricing, and promotional analytics.
Proficiency in Python, SQL, Snowflake, Azure ML/Databricks.
Practical experience with ML techniques and emerging GenAI/LLM workflows.
Strong communication and stakeholder alignment skills.
*experience may include a combination of work experience and education
Preferred Qualifications: 10-12+ years analytics experience.
Experience with agent frameworks, vector databases, hybrid search.
Experience operationalizing ML/LLM systems with CI/CD and observability.
Familiarity with Power BI and analytics experience design.
experience may include a combination of work experience and education
Competencies
Strategy & Technical Leadership - Ability to define enterprise AI strategy, set technical direction for GenAI and agentic AI programs, and guide long‑term architectural decisions.
LLMOps & Governance - Deep understanding of model/agent lifecycle management, evaluation frameworks, monitoring, guardrails, Responsible AI principles, and enterprise governance processes.
Stakeholder Influence - Strong capability to communicate complex AI concepts to executive audiences, drive alignment across product and business teams, and influence cross‑functional decisions.
AI Solution Delivery & Integration - Experience integrating models and agents into applications, microservices, or enterprise platforms (Azure, Databricks, Snowflake, Oracle AI Agent Studio).
Analytical & Systems Thinking - Strong ability to break down ambiguous problems, synth
Additional Information
At Niagara, we're looking for Team Members who want to be part of achieving our mission to provide our customers the highest quality most affordable bottled water.
Consider applying here, if you want to:
Work in an entrepreneurial and dynamic environment with a chance to make an impact.
Develop lasting relationships with great people.
Have the opportunity to build a satisfying career.
We offer competitive compensation and benefits packages for our Team Members.
Staff Data Scientist - ML, Gen AI & Agentic AI
The Staff Data Scientist is a senior individual contributor who serves as a technical lead across Machine Learning, Generative AI, and Agentic AI initiatives. The role designs, develops, and scales advanced models, RAG-powered GenAI systems, and agentic workflows that power analytics across CPG growth, demand forecasting, pricing, supply chain, and manufacturing. It emphasizes rigorous feature engineering, robust validation and deployment patterns, and clear business communication to drive adoption and value. Essential Functions
Design, build, and scale ML models for demand forecasting, growth analytics, price/pack elasticity, segmentation, trade promotion analysis, and supply-chain optimization.
Develop end-to-end ML pipelines with strong feature engineering, validation, deployment, and model monitoring/observability.
Deliver interpretable, production-ready models embedded into analytics products and decision experiences.
Build RAG-powered GenAI solutions with retrieval design, prompting strategies, grounding, and evaluation frameworks.
Develop tool-using and orchestrated agentic workflows to accelerate analytics and automate decision support.
Partner with APM&I/product management and business leaders to translate prioritized use cases into measurable outcomes; DS owns the analytic/agent approach and validates performance; APM&I owns value framing and business sign-off.
Communicate complex ML/GenAI concepts clearly to technical and business stakeholders, including model behavior, risks, and trade-offs.
Implement Responsible AI practices covering safety, bias mitigation, privacy, evaluation, and telemetry.
Provide technical leadership and mentorship without direct reports, guiding best practices, reviewing code/approaches, and elevating team capability.
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.
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.
Niagarawater · Corp-main - Diamond Bar, CA