Customer Service Analytics & Insights Analyst

Join a data-driven team focused on improving customer service operations through advanced analytics, demand forecasting, and customer insights. In this role, you will combine analytical judgment with operational expertise to anticipate customer service demand and understand the factors driving customer contacts. You will interpret forecasting models, assess emerging trends, and evaluate the impact of product launches, pricing changes, policy updates, and unexpected events. By connecting operational forecasts with customer experience insights, you will help teams make more informed decisions about staffing, capacity planning, and service improvements. You will also leverage Generative AI and conversation intelligence tools to uncover patterns, automate repetitive tasks, and improve analytical workflows. This remote opportunity is ideal for a curious, independent analyst who enjoys transforming complex data into clear recommendations with measurable business impact.

- Education: Bachelor's degree in Mathematics, Statistics, Economics, Finance, Engineering, Data Science, or another quantitative discipline, or equivalent practical experience.

- Professional experience: At least 4 years of experience in analytics, customer insights, research, forecasting, workforce management, or contact center analytics, with a demonstrated ability to turn data into actionable business recommendations.

- Technical expertise: Proficiency in SQL and spreadsheet modeling, with the ability to investigate datasets, challenge model outputs, validate assumptions, and assess data quality rather than relying solely on automated results.

- Forecasting knowledge: Working knowledge of forecasting principles, including seasonality, event-driven demand, workload estimation, and forecast accuracy, or the ability to develop this expertise quickly.

- Customer analytics: Experience analyzing customer behavior, service interactions, or contact center data to identify contact drivers, emerging trends, operational challenges, and root causes.

- Generative AI experience: Demonstrated experience applying Generative AI tools in analytical workflows, with an interest in using AI to improve research, data interpretation, and operational efficiency.

- Communication and collaboration: Strong written and verbal communication skills, including the ability to explain forecasting changes, analytical findings, and research conclusions to non-technical audiences and senior stakeholders.

- Preferred qualifications: Direct experience interpreting or managing contact center demand forecasts, including interval-based, daily, or weekly forecasts, average handling time (AHT), and workload metrics. Familiarity with modern forecasting tools, Python or R, and statistical analysis is an advantage.

- Additional preferred experience: Background combining forecasting with customer research or insights, experience with qualitative or mixed-methods research, knowledge of natural language processing (NLP) for unstructured customer data, or experience working with outsourced and multi-vendor contact center environments.