Description

Responsibilities

 

• Work with large and complex datasets to solve challenging problems using various analytical and statistical approaches.
• Synthesize and analyze customer feedback from multiple sources (e.g., surveys, digital analytics, behavioral, and operational data) across end-to-end customer journeys to identify trends, pain points, and areas for improvement.
• Apply advanced statistical modeling, machine learning, and natural language processing (NLP) to analyze large-scale customer support interactions (e.g., chat logs, call transcripts, support tickets) and extract actionable insights.
• Use clustering and segmentation techniques to identify common customer issues and recommend targeted solutions or self-service resources.
• Develop and maintain robust reporting and dashboards to track customer experience metrics and KPIs.
• Integrate customer feedback data with other transactional, operational, and behavioral data sources to create a comprehensive picture of customer experience drivers.
• Advocate for customers and influence corrective actions through periodic and ad-hoc reporting, proactively evangelizing insights among key stakeholders.
• Collaborate with cross-functional teams to identify root causes of customer issues and develop action plans to remediate and measure effectiveness.
• Communicate complex technical concepts to non-technical stakeholders. 
  
   

Required Qualifications

 

• Degree in Analytics, Statistics, Mathematics, Computer/Data Science, Engineering, or a related field.
• Minimum 6 years of experience in data analytics, data science, or related fields.
• Less than 3 years of experience in customer experience, customer support, or customer insights analytics.
• Proficiency in crafting compelling stories using complex data sources to provide actionable insights tailored to stakeholders needs.
• Experience creating reports, visualizations, and dashboards, and communicating results and analyses to technical and non-technical audiences.
• Experience working with Customer Experience or Voice of Customer metrics (NPS, CSAT, etc.), surveys, and customer feedback.
• Strong programming skills in Python, R, and SQL.
• Proficiency in data visualization tools (e.g., Tableau, Power BI).
• Proficiency in utilizing statistical analytics techniques.
• Demonstrated ability to work collaboratively with cross-functional teams. 
  
   

Preferred Qualifications

 

• Master's or Ph.D. Degree in a quantitative field.
• Familiarity with consumer electronics or retail business.
• Proficiency in conducting predictive analytics or running ML/AL techniques.
• Experience with machine learning libraries such as Pandas, scikit-learn, TensorFlow, or PyTorch

Key Skills

Education

Master's degree