Data Analyst V

Job 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. Skills:

Very technical with marketing background Customer segmentation for marketing Customer support Comfortable with temporary tables in SQL Strong skills in Python Pandas and data structures Experience with data modeling (regression, NLP). Experience with MAANG Client Machine learning Will they have the ability to know if things go wrong using AI Use AI to accelerate the speed, but know what is being produced Customer Experience/Customer Support Preferred 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. Education/Experience:

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. Degree in Analytics, Statistics, Mathematics, Computer/Data Science, Engineering, or a related field. 6+ years of experience in data analytics, data science, or related fields. 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.