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Mid-level, common SQL/BI skillset with some AI specialization yields moderate applicant competition.
Core SQL, BI and ML skills transfer across industries, but support-operations domain knowledge adds moderate specificity.
Explicit years plus mandatory SQL, BI tooling, and ML/NLP requirements create stringent screening filters.
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Develop, implement, and report on Support, Cloud Operations, and Customer Success metrics using BI tools and AI-driven analytics.
Administer and govern analytics platforms including Google BigQuery, Looker Studio, Tableau, and Jira dashboards, ensuring data accuracy and process automation.
Leverage machine learning, predictive analytics, and generative AI to analyze support data, automate workflows, deliver insights, and manage performance reporting including monthly and quarterly metrics.
Minimum 3 years experience in data management, reporting platforms, and enterprise analytics.
Proficiency in advanced SQL techniques and experience with BI tools such as Tableau and Looker Studio.
Hands-on experience applying Generative AI, NLP, or Machine Learning to analyze unstructured support/customer data.
Education in or equivalent experience related to Customer Support industry, data analytics, or business administration.
Experienced in managing analytics in high-tech customer support or cloud operations environments.
Skilled in using advanced BI tools combined with AI and machine learning technologies to generate actionable business insights.
Able to independently lead analytics initiatives and handle data governance, audit validation, and complex dataset modeling for scalable analytics solutions.