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Customer Experience Analyst

2 weeks ago


Meerut, Uttar Pradesh, India beBeeCustomer Full time ₹ 15,00,000 - ₹ 25,00,000
Customer Experience Analyst

A leading organization is seeking a Customer Experience Analyst to join their team. In this role, you will be responsible for designing and implementing data-driven solutions to optimize customer experience metrics.

Responsibilities:

  • Design and implement data-driven solutions to optimize customer experience metrics, reduce churn, and enhance customer satisfaction using statistical analysis, machine learning, and predictive modeling.
  • Collaborate with CX teams, contact center operations, customer success, and product teams to gather requirements, understand customer journey objectives, and translate them into actionable analytical solutions.
  • Perform exploratory data analysis (EDA) on customer interaction data, contact center metrics, survey responses, and behavioral data to identify pain points and opportunities for CX improvement.
  • Build, validate, and deploy machine learning models for customer sentiment analysis, churn prediction, next-best-action recommendations, contact center forecasting, and customer lifetime value optimization.
  • Develop CX dashboards and reports using BI tools to track key metrics like NPS, CSAT, FCR, AHT, and customer journey analytics to support strategic decision-making.
  • Optimize model performance for real-time customer experience applications through hyperparameter tuning, A/B testing, and continuous performance monitoring.
  • Contribute to customer data architecture and pipeline development to ensure scalable and reliable customer data flows across touchpoints (voice, chat, email, social, web).
  • Document CX analytics methodologies, customer segmentation strategies, and model outcomes to ensure reproducibility and enable knowledge sharing across CX transformation initiatives.
  • Mentor junior data scientists and analysts on CX-specific use cases, and participate in code reviews to maintain high-quality standards for customer-facing analytics.

Requirements:

  • Proven experience (at least 6+ years) in data science, analytics, and statistical modeling with specific focus on customer experience, contact center analytics, or customer behavior analysis, including strong understanding of CX metrics, customer journey mapping, and voice-of-customer analytics.
  • Proficiency in Python and/or R for customer data analysis, sentiment analysis, and CX modeling applications.
  • Experience with data analytics libraries such as pandas, NumPy, scikit-learn, and visualization tools like matplotlib, seaborn, or Plotly for customer insights and CX reporting.
  • Experience with machine learning frameworks such as Scikit-learn, XGBoost, LightGBM, and familiarity with deep learning libraries (TensorFlow, PyTorch) for NLP applications in customer feedback analysis and chatbot optimization.
  • Solid understanding of SQL and experience working with customer databases, contact center data warehouses, and CRM systems (e.g., PostgreSQL, MySQL, SQL Server, Salesforce, ServiceNow).
  • Familiarity with data engineering tools and frameworks (e.g., Apache Airflow, dbt, Spark, or similar) for building and orchestrating customer data ETL pipelines and real-time streaming analytics.
  • Knowledge of data governance, data quality frameworks, and data lake architectures.
  • Exposure to business intelligence (BI) tools such as Power BI, Tableau, or Looker for CX dashboarding, customer journey visualization, and executive reporting on customer experience metrics.
  • Working knowledge of version control systems (e.g., Git) and collaborative development workflows for customer analytics projects.
  • Strong problem-solving skills with customer-centric analytical thinking, and the ability to work independently and as part of cross-functional CX transformation teams.
  • Excellent communication and presentation skills, with the ability to explain complex customer analytics concepts to non-technical stakeholders including CX executives, contact center managers, and customer success teams.

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