Apr 2022 – May 2023 · 1 yr 1 mo · Austin, Texas Metropolitan Area · Remote

• Collected, cleaned, and analyzed large datasets to identify trends, patterns, and insights using tools such as Excel, SQL, Python, or R.
• Developed and maintained data models, dashboards, and visualizations to communicate complex data findings to stakeholders using software like Tableau, Power BI, or QlikView.
• Conducted statistical analysis, hypothesis testing, and predictive modeling to support data-driven decision-making processes.
• Collaborated with cross-functional teams, such as marketing, sales, and product development, to understand their data needs and provide relevant insights and recommendations.
• Identified data quality issues and worked with IT teams to ensure data accuracy, completeness, and consistency.
• Created and presented reports and presentations on data findings and recommendations to senior leadership and executives.
• Stayed up-to-date with industry trends and emerging technologies related to data analytics, machine learning, and artificial intelligence to continuously improve data analysis practices and techniques.
• Conducted ad-hoc analysis and data mining to support special projects or initiatives.
• Developed and documented data analysis processes, methodologies, and best practices to ensure consistency and reproducibility of analysis results.

Sep 2021 – Apr 2022 · 7 mos · Gurugram, Haryana, India · Hybrid

• ● Managed a team of 15 to provide efficient customer support to clients.
• ● Utilized SQL-based ETL processes to generate curated data tailored to business requirements for reporting, issue handling, escalation, and stakeholder management.
• ● Analyzed business trends in the relevant domain by preparing daily, weekly, and monthly ad hoc reports using SQL and Python.
• ● Successfully identified and delivered new KPIs for business reporting, while also gathering operational requirements from stakeholders and executing on those requirements.
• ● Collaborated with cross-functional teams, including business stakeholders, project managers, and technical teams, to identify business requirements and translate them into data-driven solutions.
• ● Analyzed customer feedback and identified areas for improvement to enhance customer experience and reduce customer churn rate.
• ● Conducted root cause analysis of customer complaints and identified opportunities for process improvement to enhance customer satisfaction.
• ● Developed and maintained dashboards and reports using SQL and Python to track KPIs and performance metrics and presented insights to stakeholders on a regular basis.
• ● Conducted trend analysis and identified patterns in data to make recommendations for process improvements, cost savings, and revenue growth.
• ● Monitored and managed data quality and ensured data accuracy, completeness, and consistency across multiple systems.
• ● Developed and implemented new data visualization tools and techniques to optimize the effectiveness of data presentation and communication.

Sep 2019 – Sep 2021 · 2 yrs · India · On-site

• ● Managed auto insurance domain for a US-based Fortune 500 insurance firm.
• ● Built reports using SQL and created visually compelling presentations to facilitate data-driven business decisions in the customer service domain.
• ● Successfully delivered projects that involved sourcing data from multiple databases to build an automated reporting tool.
• ● Developed and maintained relationships with stakeholders across various departments, including customer service, operations, and IT to gather and analyze data to drive business decisions.
• ● Conducted regular meetings with cross-functional teams to discuss data insights, trends, and performance metrics to identify areas of improvement.
• ● Collaborated with IT teams to identify and resolve data quality issues to ensure accurate reporting.
• ● Developed and implemented data governance policies and procedures to ensure data accuracy, consistency, and completeness.
• ● Conducted ad-hoc analysis to support various business initiatives, including customer experience, process improvement, and cost reduction.
• ● Mentored and trained junior team members on data analysis techniques, report development, and effective communication of insights to stakeholders.