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Strong employer brand, popular Lead Data Scientist title, metro location, and broad technical requirements.
Core ML and analytics skills transfer across industries, though CX/contact-center domain experience adds sensitivity.
Explicit 6-8 years requirement plus mandatory Python, SQL, and ML skills drives high shortlisting strictness.
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Lead development of customer contact analytics to identify pain points and drivers of customer issues and escalations.
Build and maintain a Predictive Escalation Model to proactively identify accounts and issues at risk of escalation.
Collaborate with CX, Product, and Engineering teams to translate insights into actionable business outcomes like contact reduction and faster resolution.
6-8+ years of experience in Data Science, Advanced Analytics, or Applied Machine Learning.
Advanced proficiency in Python and SQL; experience with data science libraries such as pandas and scikit-learn.
Experience working with large, operational or customer-facing datasets and familiarity with at least one cloud data platform (GCP, Azure, or AWS).
Work Experience Required: 6-8+ years in relevant fields.
Experienced senior individual contributor comfortable with technical leadership and owning end-to-end analytical outcomes.
Proven ability to translate complex data science work into clear business decisions and actionable insights for senior stakeholders.
Domain experience in customer experience analytics or contact center data preferred, with practical exposure to operationalizing predictive models for customer escalation risk.