Data Analyst
Upwork, Fiverr, Freelancer
Total years of experience :22 years, 2 Months
City: Delhi Country: India
• Develop interactive dashboards and reports using Tableau and Power BI to visualize complex datasets and communicate insights efectively.
• Design intuitive visualizations that facilitate data-driven decision-making and drive business outcomes.
• Customize dashboards to meet specific stakeholder needs and preferences, ensuring clarity and usability.
• Customize visualizations based on feedback and evolving business requirements, maintaining accuracy and relevance.
• Ensure data quality and integrity by implementing data validation checks and error handling mechanisms in SQL, Pandas, SAS and Spark SQL.
• Work closely with cross-functional teams, including data engineers, business analysts, and decision-makers, to understand data needs and requirements.
• Communicate findings, insights, and recommendations to technical and non-technical stakeholders in a clear and concise manner.
• Collaborate with business stakeholders to define key performance indicators (KPIs) and metrics for measuring the success of analytical solutions.
• Participate in team meetings, brainstorming sessions, and knowledge-sharing activities to foster a collaborative and innovative environment.
Python, SAS, Tableau, Power BI, SQL, Advance Excel.
Project Name: Global Merchant Network Services Domain: Retail Client: AMEX
Description: Global Merchant Dashboard and Optimization.
Roles and Responsibilities:
• Led the conception, design, and implementation of a comprehensive Tableau dashboard catering to global merchant operations. Incorporated key performance indicators (KPIs) and visualizations that provided real time insights into sales, transaction trends, and regional performance, empowering leadership with a holistic view of merchant activities.
• Spearheaded optimization initiatives based on data-driven insights derived from the Tableau dashboard. Implemented targeted strategies to enhance merchant onboarding, identify high-performing regions, and optimize transaction processes, resulting in a measurable improvement in overall merchant satisfaction and revenue growth.
• Established robust SQL-based data quality checks, ensuring the accuracy, completeness, and consistency of datasets. Implemented a suite of SQL queries to identify and rectify anomalies, missing values, and outliers, significantly enhancing the reliability of the overall data infrastructure.
Project Name: Net Promoter Score Domain: Automobile/BPO Client: Maruti-Suzuki India Limited
Description: Net Promoter Score.
Roles and Responsibilities:
• Led the development and implementation of a comprehensive NPS reporting solution in Power BI, providing end-to-end visibility into customer satisfaction metrics. This included designing data models, integrating survey data, and creating a dynamic and intuitive dashboard.
• Successfully integrated NPS data from diverse sources, such as customer surveys, support interactions, and other feedback channels, into a unified Power BI platform. Ensured seamless collaboration with cross functional teams to gather and consolidate relevant data.
• Implemented interactive features and drill-down capabilities within the NPS Power BI report, enabling stakeholders to explore and analyze customer satisfaction trends at various levels of granularity. This facilitated a deeper understanding of the factors influencing NPS scores.
• Applied advanced analytics techniques within Power BI to conduct trend analysis on NPS scores over time. Developed predictive models to anticipate changes in customer sentiment, enabling proactive strategies for maintaining or improving NPS.
• Established automated reporting mechanisms in Power BI for regular distribution of NPS insights to key stakeholders. Integrated alerting systems to notify teams in real-time of significant changes in NPS, fostering a proactive approach to addressing customer satisfaction challenges
Project Name: Binary Classification using Random Forest Domain: Banking Client: Axis Bank
Description: Fraud Analytics
Roles and Responsibilities:
• Data Extraction and validating the datasets via SQL Server DB.
• Sanity check and data preparation via Panda in Python.
• Predictive Analytics using Logistic Regression, and Random Forest using Python.
• Measurement Techniques Confusion Matri x ( F1 Score).
• On the Basis Best F(Beta) Score, Selecting the Random Forest Model.
• The process helps in Detecting Real-Time Fraud and Helped the organization to reduce online fraud by saving upto INR 15, 00, 00, 000/ Per Annum.
City: New Delhi | Country: India
Project Name: Binary Classification using Random Forest Domain: Banking Client: Axis Bank
Description: Fraud Analytics
Roles and Responsibilities:
➢ Data Extraction and validating the datasets via SQL Server DB.
➢ Sanity check and data preparation via Panda in Python.
➢ Predictive Analytics using Logistic Regression, and Random Forest using Python.
➢ Measurement Techniques Confusion Matri x ( F1 Score).
➢ On the Basis Best F(Beta) Score, Selecting the Random Forest Model.
➢ The process helps in Detecting Real-Time Fraud and Helped the organization to reduce
online fraud by saving upto INR 15, 00, 00, 000/ Per Annum
Project Name: Churn Analysis Domain: Telecom (Vodafone, AT&T ) Client: Matrix Cellular International Services Limited
Description: Churn Analysis of Diferent Product Categories (International Data Card, International & Domestic SIM CARD, International Travel Insurance & Amex Credit Cards and Forex Cards).
Roles and Responsibilities:
• Led a comprehensive Churn Analysis project focused on diverse product categories, including International Data Card, International & Domestic SIM CARD, International Travel Insurance, Amex Credit Cards, and Forex Cards.
• Developed and implemented a dynamic Power BI report showcasing insightful visualizations for churn rates, time trends, and customer segmentation across diferent product categories.
• Utilized advanced predictive modeling techniques within Power BI to forecast churn, providing actionable insights for strategic decision-making and proactive customer retention strategies.
• Collaborated with cross-functional teams to integrate data from multiple sources, ensuring a robust and accurate data model for the Churn Analysis in Power BI.
• Provided data-driven recommendations based on the Churn Analysis, contributing to improved customer retention strategies and the overall success of the business. Demonstrated the ability to translate complex insights into actionable steps for stakeholders.
Client : Bharti-Airtel (Network Surveillance)
Description: Identifying the most frequent Network Incidents issues in the Bharti-Airtel Network and making the network more efficient by Aggressive diagnostic of such issue.
Roles and Responsibilities:
•Extracting and validating the datasets via SQL Server and comparing the results to the expected output.
•Extracting and validating the datasets and comparing the results to the expected output.
•Publish Pareto Analysis Visualization and highlighting the problematic network issues to Network
- Network Change Management.
- Network Change Management, BMC Remedy ITSM.
- Network Surveillance.
- Pareto Analysis using SAS EG.
- Network Reporting and Escalation Matrix.
City: Gurugram Country: India
- Network Change Management.
- Network Change Management, BMC Remedy ITSM.
- Network Surveillance.
- Pareto Analysis using SAS EG.
- Network Reporting and Escalation Matrix.
Network Surveillance, ITSM, BMC Remedy, Change Management and Incident Management.
- Network Change Management.
- Network Change Management, BMC Remedy ITSM.
- Network Surveillance.
- Pareto Analysis using SAS EG.
- Network Reporting and Escalation Matrix.
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•Network Surveillance/Testing of Bharti Airtel Limited PAN India Network (Huawei/Tellabs/Alcatel/Nortel/ECI) Including SDH/DWDM.
•Network Incident/Change Management of Bharti Airtel TNG Optical Fiber Network
•Preparing Network SLA Report & Pareto Analysis of Network Incident
•Preparing performance reports of NOC Engineers and Zonal - Network Field Engineer Teams.
•Project Name: Sales/Revenue Forecasting Models
