Data Scientist – AI and Business Intelligence

Requirements

Must have:– 2–6 years of enterprise-level experience in applied data science or analytics with delivery to stakeholders – Bachelors or Masters degree in Data Science, Computer Science, Statistics, Operations Research, or equivalent practical experience; portfolio or Git Hub examples preferred – Strong command of Python (pandas, sklearn) and SQL, with a solid foundation in statistics and experimental methods (forecasting, power analysis, standard tests) – Proven experience deploying models or analytics into business workflows (e.g., CRM scoring, operational forecasting, dashboards) – Familiarity with concepts related to LLM (prompting, retrieval, evaluations) and a quality-driven approach – Working knowledge of MLOps/LLMOps and Git-based workflows, encompassing versioning, automated evaluations/regression tests, monitoring/alerting, and documentation strategies

Responsibilities:

• Define evaluation strategies for LLM/RAG/agents, focusing on groundedness, helpfulness, safety, regression testing, and release criteria – Build and maintain benchmark datasets and scoring criteria for agent performance across critical use cases – Establish monitoring protocols for agent outcomes including quality, latency, cost, drift, user feedback, and business KPIs – Collaborate with the AI Applications Engineer on prompt strategies, retrieval patterns, tool usage, and safe fallbacks – Conduct red team/adversarial testing and implement mitigations for unsafe or low-quality behavior – Ensure privacy and security by design, including PII minimization, role-based access control, and auditable deletions – Define human-in-the-loop processes when necessary for sampling, review queues, and labeling guidelines – Manage the LLM release procedure including prompt/model/versioning, offline evaluations, staging, and rollbacks – Maintain documentation for production AI models and metrics, including evaluation reports and failure modes – Implement automated regression checks to avoid quality or safety regressions during deployments – Define incident response protocols for addressing agent-related issues including triage and corrective actions – Partner with cross-functional teams to turn inquiries into actionable plans, success metrics, and data-driven recommendations – Lead predictive modeling for BI priorities such as scoring, demand planning, and forecasting – Design and conduct experiments (A/B testing, holdouts) with appropriate power and instrumentation – Define business and model metrics;
  
  establish golden labels and decision thresholds with measurable ROI – Work on feature engineering through Salesforce, Net Suite, Five9, and other data sources, collaborating with Data Engineering for operationalization – Translate modeling results into operational procedures for scoring, routing, and dashboard alerts – Contribute to BI and analytics tasks as needed to ensure that outcomes are measurable and actionable – Enhance data clarity through metric definitions, data quality checks, and stakeholder engagement – Undertake additional assigned duties as necessary

Company:

At Sunlighten, we are dedicated to enhancing lives through innovative health and wellness solutions, focusing on infrared sauna therapy. As we celebrate 25 years of growth from our Kansas City origins to a global presence, we are eager to welcome a talented Data Scientist, AI & BI to our team. In this dynamic role, you will help drive significant impacts across various departments by utilizing applied machine learning and analytics.

We offer a collaborative and innovative workplace, opportunities for career advancement in our rapidly growing wellness technology sector, and a comprehensive benefits package including competitive paid time off, on-site fitness facilities, health insurance options, and opportunities for professional development.

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