Senior Analyst - CX

Neuiq Technologies; Mumbai; On-site; INR 3,000,000 - 6,000,000; Full time

Job summary

Neuiq Technologies is seeking a senior analytics leader to advance CX360 capabilities, building health scores, churn and renewal risk models, and customer segmentation. You will partner with Data Science, Product, Engineering, and Finance to deliver decision-ready insights and scalable governance across enterprise BI tools.

The role emphasizes NLP, LLM-driven analytics, and production-ready dashboards that translate analytics into prioritized actions for retention and efficiency improvements.

Qualifications

• Bachelor's degree in a quantitative field required.
• 6+ years in advanced analytics, customer intelligence, enterprise BI, or CX measurement roles within SaaS or complex customer environments.
• Experience designing and governing scoring frameworks, driver analysis models, or prioritization methodologies tied to measurable revenue and retention outcomes.
• Proven experience building and deploying predictive models (e.g., churn probability, renewal risk, expansion propensity) that informed real business decisions.
• Operationalizing AI- and LLM-driven analytics within enterprise decision workflows — not just experimentation or prototype analysis.
• Experience applying NLP and machine learning techniques to large-scale unstructured customer feedback and behavioral datasets.
• Experience partnering with Data Science, Engineering, Product, and Finance to move models from concept to production deployment.
• Strong experience designing executive-facing data visualizations and translating statistical findings into prioritized, decision-ready recommendations.
• Demonstrated ability to connect customer experience and analytical outputs directly to GRR, CPO, CSAT, operational efficiency, and cost-to-serve metrics.

Responsibilities

• Ensure CX360 delivers accurate, trusted, decision-ready customer intelligence across Product, CX, Operations, and executive leadership, with clear ownership of scoring integrity.
• Define and govern scoring frameworks, lifecycle metrics, friction models, and prioritization thresholds to ensure consistency, transparency, and business relevance.
• Collaborate with Data Science, Architecture, Engineering, and Product to validate data integrity and strengthen insights through predictive modeling and sentiment analysis.
• Build and evolve customer intelligence analytics including segmentation, cohort analysis, and driver attribution tied directly to retention and efficiency outcomes.
• Quantify the financial and operational impact of customer friction using revenue and cost modeling to establish measurable prioritization standards.
• Translate complex analytics into structured, prioritized recommendations that influence retention strategy, roadmap investment, and operational optimization.
• Apply AI techniques including NLP, LLM integrations, and predictive models to automate feedback classification, improve signal detection, and reduce time-to-insight.
• Maintain governed analytics environments across Qualtrics, Snowflake, Power BI, Tableau, and related systems to ensure secure, scalable enterprise intelligence.

Skills

Data Science

Statistics

Machine Learning

Churn modeling

Retention analytics

NLP

LLM integration

Executive dashboards

Predictive modeling

Cohort analysis

Education

Bachelor's in quantitative field

Tools

Qualtrics

Snowflake

Power BI

Tableau

Job description

Role & responsibilities

Role Overview:

This role is part of the Customer Experience team and focuses on using data and AI to improve customer retention and experience. You'll build customer health scores, churn and renewal risk models, customer segmentation, and executive dashboards while partnering with Data Science, Product, Engineering, and Finance teams.

Preferred candidate profile

Key Responsibilities:

• Ensure CX360 delivers accurate, trusted, decision-ready customer intelligence across Product, CX, Operations, and executive leadership, with clear ownership of scoring integrity.


• Define and govern scoring frameworks, lifecycle metrics, friction models, and prioritization thresholds to ensure consistency, transparency, and business relevance.


• Collaborate with Data Science, Architecture, Engineering, and Product to validate data integrity and strengthen insights through predictive modeling and sentiment analysis.


• Build and evolve customer intelligence analytics including segmentation, cohort analysis, and driver attribution tied directly to retention and efficiency outcomes.


• Quantify the financial and operational impact of customer friction using revenue and cost modeling to establish measurable prioritization standards.


• Translate complex analytics into structured, prioritized recommendations that influence retention strategy, roadmap investment, and operational optimization.


• Apply AI techniques including NLP, LLM integrations, and predictive models to automate feedback classification, improve signal detection, and reduce time-to-insight.


• Maintain governed analytics environments across Qualtrics, Snowflake, Power BI, Tableau, and related systems to ensure secure, scalable enterprise intelligence.

Key Skills:

• Bachelors degree in Data Science, Statistics, Mathematics, Computer Science, Economics, Engineering, or a related quantitative discipline required.


• 6+ years of progressive experience in advanced analytics, customer intelligence, enterprise BI, or CX measurement roles within SaaS or complex customer environments.


• Demonstrated experience designing and governing scoring frameworks, driver analysis models, or prioritization methodologies tied to measurable revenue and retention outcomes.


• Proven experience building and deploying predictive models (e.g., churn probability, renewal risk, expansion propensity) that informed real business decisions.


• Demonstrated experience operationalizing AI- and LLM-driven analytics within enterprise decision workflows — not just experimentation or prototype analysis.


• Experience applying NLP and machine learning techniques to large-scale unstructured customer feedback and behavioral datasets.


• Experience partnering with Data Science, Engineering, Product, and Finance to move models from concept to production deployment.


• Strong experience designing executive-facing data visualizations and translating statistical findings into prioritized, decision-ready recommendations.


• Demonstrated ability to connect customer experience and analytical outputs directly to GRR, CPO, CSAT, operational efficiency, and cost-to-serve metrics.