As an integral part of the fast‑growing **CallMiner Customer Success Team**, the **Business Analyst 2** plays a pivotal role in implementing and optimizing **CX automation solutions fueled by AI‑powered conversation intelligence**. By leveraging **machine learning (ML)**, **natural language processing (NLP)**, and advanced data modeling, this analyst drives automation strategies that convert raw omni‑channel customer interaction data into streamlined processes, predictive workflows, and actionable insights for measurable ROI and transformational customer experience improvements. This position combines **expert business/data analysis** with **CX automation design**, AI/ML model evaluation, and change‑management leadership — ensuring customers follow best practices, accelerate adoption, and achieve “speed to value” through the CallMiner platform. A balance of **technical acumen, AI experience, and exceptional communication skills** is essential. **Primary Responsibilities** - Conduct thorough quality control & peer review of AI-generated insights and analytics dashboards. - Mentor a network of power users, teaching advanced search techniques, AI-powered categorization, and real-world application of ML/NLP components in the CallMiner platform. - Configure customer databases within the CallMiner User Interface, including query building, AI-driven pattern tuning, and model optimization to improve recognition of language patterns for business insights. - Collaborate with data science and AI engineering teams to design, test, and refine ML models for sentiment analysis, intent detection, and conversational trends. - Implement automated scoring & topic identification using AI-based analysis across audio, chat, social media, and email to uncover trends, predictors, and opportunities for strategic action. - Configure Search‑Based Categories and ML‑tuned rules to optimize automated decision‑making and alert generation - Deliver high-quality Professional Services projects (primarily advanced AI-backed data analyses) aligned with scope, timelines, and ROI expectations. - Evaluate AI model performance metrics (precision, recall, F1 score) and provide recommendations for improvement. - Apply predictive analytics to forecast customer needs, churn risk, and operational improvements. - Deeply understand metadata, Key Performance Indicators, and AI-derived insights; configure Search-Based Categories using optimal keyword and ML-tuned parameters. - Compile observation reports and deliver briefings utilizing deep dive, root cause, SWOT, regression, and AI-enhanced statistical methodologies. - Drive customer value by delivering quantifiable results and recommending AI-informed organizational change initiatives. - Provide thought leadership on AI-powered use cases and emerging trends in conversational intelligence. - Communicate barriers impacting AI adoption or customer success to management, including recommended solutions. - Contribute to enablement content, training sessions, certification programs, thought leadership materials, webinars, and conference presentations focused on **automating customer experience using conversation intelligence**. - Mentor and train newer analysts in both traditional analytics and AI-driven methodologies.