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Mid-level ML/NLP role in a metro with broad requirements increases applicant competition substantially.
Technical ML, NLP and MLOps skills are transferable, though BPO/CX domain knowledge moderately reduces portability.
Explicit 5–7 years plus mandatory ML, NLP, R/Python, SQL and AWS MLOps increases strictness.
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Develop and maintain predictive and diagnostic models to improve call centre operations and customer experience within BPO environments.
Conduct optimisation analytics focused on workforce, cost, and service performance to enhance operational efficiency.
Collaborate with team leads and client consultants to define analytical requirements and translate complex analysis into clear insights for stakeholders.
5–7 years of experience in data science or advanced analytics, preferably in BPO, call centre, or customer experience sectors.
Proficiency in R (preferred) or Python, plus SQL.
Graduate degree required.
Experience or familiarity with NLP, text analytics, and MLOps practices in AWS environments.
Experienced in customer experience and operational performance analytics within BPO or call centre contexts.
Skilled in both predictive modelling and optimisation analytics to drive business impact in client-facing roles.
Comfortable working with complex data and translating technical outputs into actionable client insights.