I am passionate, dependable and adaptable Data Analyst, leveraging over 5 years of corporate expertise in spearheading Advanced Analytics & Business Intelligence initiatives across diverse domains including Retail, BFSI, Pharmaceuticals, & Healthcare.
- Masters of Business Administration (2011) Rourkela Institute of Management Studies, Rourkela, India
- Bachelors of Commerce (2009) Utkal University, Bhubaneswar, India
Data Analysis | Data Visualization | Power-BI | Team Handling | UX Design | SQL | Tableau | Alteryx | Azure | Python | SAS | Data Modelling | DAX
- Streamlined a manual data extraction process, resulting in a 7% reduction in processing time and 24% improvement in accuracy.
- Trained cross-functional teams to identify and resolve data-related issues, resulting in a 15% improvement in data accuracy.
- Simplified data cleansing steps to reduce bad data by 20% which significantly led to $75k cost savings. Analyzing data through extraction from preferred data sources.
- Restructured communication flow among 4 departments while cutting down manual documentation by 75%.
- Devised and executed a data cleaning approach that involved removing outliers and filling null values enabling 20% improvement in data quality. Carrying out all data analytics tasks
- Automated a visualization of the current sales and revenue pipeline using data visualization & SQL on multiple datasets with over 10 mn+ rows.
- Reduced manual document processing time by 50% in three months, resulting in increasing efficiency.
- Identified steps to reduce data error rates by 14% resulting in 20x cost savings to the client.
- Designed and implemented process changes that improved customer experience by 27%.
- Conceived an innovative documentation strategy and task monitoring system in HRIS that increased annual project revenue by 35%. Ensuring data is in good shape by cleansing the raw data as per the guidelines.
- Offered technical support for system and internet issues in both consumer and corporate environments for US-based clients.
- Followed-up service tickets into the incident tracking system to facilitate 10x faster problem identification and resolution.
- Led financial collections for B-2-B clients, ensuring prompt payments and minimizing debts.
- Analyzed data from 25k monthly active users and used outputs to guide marketing and product strategies.
- Incorporated various means of data modeling techniques using ETL tools to get the desired business results to take informed data-driven decisions.
- Drove redevelopment of internal tracking system for internal use by 150 employees, resulting in reduction of 20% production hours.
- Governed a 6 member cross-functional team and co-ordinated with 4 business-partners towards the successful launch of an e-commerce platforms.
Link-https://www.novypro.com/profile_about/arunav Duration: Jan 2022 - Mar 2022
Objective: To segment customers based on their purchasing behavior & demographics to target marketing campaigns more effectively. Application based utilization :
- Excel: Used for data cleaning, data exploration, and basic analysis.
- Power BI: Created visualizations and interactive dashboards to visualize customer segments.
- SQL: Extracted and transformed data from a relational database.
- Python: Utilized machine learning algorithms for clustering analysis. SAS: Conducted statistical analysis and generated.
Link-https://www.novypro.com/profile_about/arunav Duration: Mar 2022 - Jun 2022
Objective: To detect fraudulent transactions & implement measures to prevent financial losses.
- Excel: Analyzed transaction data and identified patterns and anomalies.
- Power BI: Visualized transaction patterns and created dashboards to monitor fraud alerts.
- SQL: Extracted and transformed transaction data from a database.
- Python: Developed machine learning models for fraud detection using classification algorithms.
- SAS: Conducted statistical analysis to identify unusual patterns and generate fraud risk sc
Link - https://www.novypro.com/profile_about/arunav Duration: Jun 2022 - Aug 2022
Objective : To analyze sentiment patterns on social media platforms to understand customer opinions & improve brand reputation. Below are some of the factors how we utilized the applications:
- Excel: Pre-processed and cleaned raw social media data.
- Power BI: Created visualizations to analyze sentiment trends and identify influential topics.
- SQL: Stored and queried social media data in a database for efficient analysis.
- Python: Utilized natural language processing techniques to analyze sentiment
Google Data Analytics Professional Certificate
- Coursera • 01/2022
Data Analytics For Decision Making
- Bond University • 08/2020
Microsoft Certified: Azure Data Fundamentals
- Microsoft • 08/2022
Google Project Management Professional Certificate
- Coursera • 02/2022
Six Sigma: Black Belt
- LinkedIn • 06/2023
Microsoft Certified: Power BI Data Analyst Associate
- Microsoft • 12/2021
Data Analyst Certification
- ExcelR • 03/2023
Cert Prep: Certified Analytics Professional (CAP)
- LinkedIn • 06/2023
MS SQL Developer
- Intelipaat •08/2022
IBM Data Visualization Certificate
- IBM Skills Network • 06/2023
Certified Analytics Professional
- LinkedIn • 06/2023