Job Description
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.
Job Tags
Remote job, Temporary work