Seeking an experienced ML Engineer to analyze call center transcripts and customer data using NLP and machine learning. The candidate will build and deploy models that drive churn reduction, personalization, and campaign optimization. Strong Python proficiency and machine learning experience required.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
ML Engineer โ NLP & Customer Analytics
Location: 100% Remote (US-based, Onshore Only)
Duration: 8 Months contract (possible extension)
Note: Need someone with telecom background experience.
Position Overview
Seeking an experienced ML Engineer to analyze call center transcripts and customer data using NLP and machine learning. The candidate will build and deploy models that drive churn reduction, personalization, and campaign optimization โ working across structured and unstructured data sources including usage, billing, CRM, and call logs.
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Key Responsibilities
Analyze call center transcripts using NLP to detect customer sentiment, intent, churn risk, complaints, and upsell/cross-sell opportunities. Develop and maintain models for churn prediction, Next Best Offer/personalization, and campaign targeting and uplift. Build customer segments and propensity models. Support A/B testing and campaign optimization initiatives. Deploy and monitor ML models in production environments.
Required Skills and Qualifications
Strong Python proficiency โ Pandas, Scikit-learn, PyTorch, or TensorFlow Machine learning and NLP experience SQL and data handling skills Experience working with customer and marketing data Ability to work with unstructured data (text, transcripts, call logs)
Good to Have
Telecom or subscription business experience Experience with recommendation systems or uplift modeling Familiarity with speech or call center analytics
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Work Location and Equipment
100% Remote โ US-based, onshore only Laptop provided Communication via Microsoft Teams
PriceSenz is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, or disability.
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