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Data Analyst - Customer Experience

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Onsite

Data Analyst - Customer Experience

Creospan Inc.

Data Analyst - Customer Experience

Skills

SQL QueriesPythonData SciencepandasPyTorchTensorFlowRData AnalysisMachine LearningAINLP / Natural Language ProcessingCustomer Support

9 days ago

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Important information


Contract type:

Freelance / Contract

Location:

United States

Work mode:

Onsite

Published on:

15 October 2026

What they need


Creospan is a growing tech collective of makers, shakers, and problem solvers, offering solutions today that will propel businesses into a better tomorrow. “Tomorrow’s ideas, built today!” In addition to being able to work alongside equally brilliant and motivated developers, our consultants appreciate the opportunity to learn and apply new skills and methodologies to different clients and industries.

******NO C2C/3RD PARTY, LOOKING FOR W2 CANDIDATES ONLY, must be able to work in the US without sponsorship now or in the future***

Responsibilities

● Work with large and complex datasets to solve challenging problems using various analytical and statistical approaches.

● Synthesize and analyze customer signals 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.

● Integrate customer feedback data with other transactional, operational, and behavioral data sources to create a comprehensive picture of customer experience drivers.

● Use various statistical techniques to surface and rank the drivers of core and inferred metrics, separating meaningful signal from noise.

● Define, test, and launch a comprehensive customer support and CX metric scorecard that tracks key performance indicators, uncovers underlying operational and experiential drivers across digital, AI, and human assisted support

● Demonstrate the ROI of CX by establishing the relationship between customer metrics and business outcomes.

● Design, prompt, and orchestrate AI systems to automate data analysis, synthesize insights, and execute multi-step analytical tasks (e.g., prompting agents to run analysis, clean datasets, or build visualizations).

● Advocate for customers and influence corrective actions through periodic and ad-hoc reporting, proactively evangelizing insights among key stakeholders.

● Communicate complex technical concepts to non-technical stakeholders.

Required Qualifications

● Degree in Analytics, Statistics, Mathematics, Computer/Data Science, Engineering, or a related field.

● 8+ years of experience in data analytics, data science, or related fields.

● 2+ 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 working with Customer Experience or Voice of Customer metrics (NPS, CSAT, etc.), surveys, and customer feedback.

● Strong programming skills in Python, R, and SQL.

● Strong proficiency in utilizing statistical analytics techniques (e.g., correlation analysis, multivariate regression, and feature-importance methods).

● Proficiency in conducting predictive analytics or running ML/AL techniques.

● Proficiency in AI-powered tools and demonstrated working knowledge of Generative AI technologies for analytics and reporting (e.g., LLMs and AI agents).

● 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.

● Experience with machine learning libraries such as Pandas, scikit-learn, TensorFlow, or PyTorch.

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