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Mid-level, metro ML role with common data science skills and multiple amplifiers causing high competition.
Preference for BPO/call-centre domain experience and telephony tools increases industry-specific background sensitivity.
Explicit 5–7 years plus required ML, NLP, AWS/MLOps and BPO/call-centre tool experience enforces high filter strictness.
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Develop and maintain predictive and diagnostic models to enhance call centre operations and customer experience in BPO environments.
Perform optimisation analytics to improve workforce efficiency, cost management, and service performance.
Deliver actionable customer analytics and collaborate with client-facing teams to translate complex data 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, and SQL.
Experience with predictive modelling, diagnostic analytics, optimisation, growth analytics, NLP, and text analytics.
Graduate degree required; familiarity with Amazon Connect or Genesys Cloud CX and MLOps in AWS is noted but not mandatory.
Experienced in handling complex analytics projects supporting customer experience and operational performance in BPO or call centre contexts.
Skilled in translating data science outputs into clear presentations for non-technical stakeholders and working collaboratively with client-facing teams.
Familiar with AI/Analytics practices focused on customer retention, churn, and revenue growth analytics.