Join an innovative Data Science team focused on the Contact Center domain, dedicated to revolutionizing customer interactions through data-driven intelligence. Within the Marketing Analytics team, we optimize contact center operations by leveraging machine learning, natural language processing (NLP), generative AI, and advanced analytics.

Our work involves analyzing customer conversations, predicting user behavior, and enhancing self-service capabilities to reduce call transfers and improve satisfaction. We build conversational AI models, real-time recommendation systems, and predictive analytics solutions that drive significant business impact. By integrating AI-driven insights with marketing strategies, we enable proactive customer engagement, personalized experiences, and operational efficiencies across various touchpoints.

This role focuses on driving strategic initiatives, managing business transformations, and utilizing industry expertise to develop value-driven solutions. You will be instrumental in applying data science to solve real-world customer experience challenges.

Key responsibilities include extracting strategic insights from large datasets, applying statistical, machine learning, and AI techniques, and proficiently handling data using Python, Spark, or SQL. Clear communication of ideas and results to non-technical stakeholders is essential. You will also need a strong aptitude for placing quantitative analysis within the context of marketing and business economics, alongside proficiency in visualization tools like Tableau or Power BI.

The ideal candidate possesses a Master's degree in computer science, statistics, applied mathematics, or a related field with at least 2 years of experience, or a Bachelor's degree in a similar field with 3+ years of experience. Experience in Health Analytics is a prerequisite.

We are seeking individuals adept at using statistical methods (forecasting/modeling, optimization), machine learning (GBM, Decision Trees), and AI techniques (Deep Learning). Proficiency in data handling with Python, Spark, SQL, or similar packages is required. Excellent written and oral communication skills are necessary to effectively convey complex ideas to business audiences. A strong interest in applying quantitative analysis to marketing and business economics is also crucial, as is familiarity with visualization tools such as Tableau or Power BI.