PhonePe Recruitment Drive | Hiring MIS Analyst Fresher / Experienced

• Bachelor’s degree in Data Science, Statistics, Business Analytics, or a related field. A master’s degree is a plus.
• Proven experience as a Data Analyst, preferably within a customer experience or marketing context.
• Strong proficiency in data analysis tools and languages such as SQL, Python, or R.
• Experience with data visualization tools like Tableau, Power BI, or similar.
• Familiarity with customer experience metrics and methodologies is preferred.
• Strong communication and storytelling skills, with the ability to present complex data insights to non-technical stakeholders in an engaging manner.
• Ability to work independently and collaboratively in a fast-paced environment.

As a Data Insights Analyst specializing in Customer Experience (CX), you will play a crucial role in transforming data into compelling stories that drive our customer engagement strategies. You will analyze customer data to identify trends, patterns, and opportunities for improving customer satisfaction and loyalty. Your analytical skills and storytelling abilities will help shape the overall customer experience and influence business decisions.

Key Responsibilities:

• Data Analysis: Collect, process, and analyze large datasets related to customer interactions and feedback. Identify trends, patterns, and insights to improve the customer experience.
• Storytelling with Data: Craft compelling narratives from data insights that effectively communicate the story behind the numbers. Engage stakeholders by presenting data-driven stories that inspire action and change.
• Reporting and Visualization: Develop and maintain dashboards and reports to communicate insights to stakeholders. Use data visualization tools to present complex data in an easily understandable format.
• Customer Insights: Work closely with the CX team to identify areas for improvement and innovation in the customer journey. Provide insights to enhance customer satisfaction and retention.
• Collaboration: Partner with cross-functional teams, including marketing, product development, and customer service, to ensure a holistic approach to customer experience improvements.
• Predictive Modeling: Utilize predictive analytics to forecast customer behavior and trends. Develop models to identify potential risks and opportunities.
• Performance Metrics: Establish and monitor key performance indicators (KPIs) related to customer experience. Track the impact of implemented strategies and recommend adjustments as needed.
• Continuous Improvement: Stay updated with industry trends and best practices in data analytics and customer experience. Propose innovative solutions to enhance data analysis processes.
• Decision\ making,