The role involves conducting multiple analyses throughout the year to address business challenges across the client life cycle, including acquisition, engagement, and retention. The analyst will leverage various analytical approaches and techniques to process diverse data sources, such as client profiles, transaction records, and unstructured call transcripts. The position requires converting complex business problems into structured analytical frameworks to provide data-driven insights to stakeholders. Additionally, the role entails building predictive models and developing solutions to support business functions. The analyst will also contribute to the design of go-to-market strategies for a wide variety of business issues.

Candidates must possess a Bachelor’s degree with at least three years of experience or a Master’s degree with at least two years of experience in data analytics. Required technical proficiencies include Python, R, PySpark, Hive, MS Excel, and PowerPoint. Applicants must demonstrate the ability to apply predictive modeling and NLP techniques to structured and unstructured data. Strong analytical, problem-solving, and communication skills are essential for success in this matrix environment.