BUSINESSANALYST Resume

TECHNICAL SKILLS

Expert: Data Analytics, Business Intelligence, Predictive Analysis, Data Models, Statistics

Programming: Python, R, SQL, Excel ((VLOOKUP, Pivot Tables, Charts, Macros), SAS, HTML, VBA, SPSS

Database Skills: MySQL, MS SQL, MS Access, Hadoop, Hive, PostgreSQL, T - SQL, Oracle SQL, Mondo DB, KSQL

Visualization: Tableau, Power BI, QlikView, Qlik Sense, Alteryx, Looker, MicroStrategy, SSRS

Proficiency: Optimization, Supply Chain Management, KPI Strategy, Data Mining, Data Migration, Wrangling, Agile, Business Requirements & Analysis, Project Management, Web Analytics, HR Analytics, Data Reporting, ETL Framework, Mix Model, Bayesian Regression, Graphic Model, Communication Skills, Interpersonal Skills, Teradata, Problem Solving, Customer Service, Agile Methodology, Database Design, Segmentation Techniques, Software Development Life Cycle, cohort analysis, A/B Testing, Hypothesis Testing, VBA, SharePoint, CRM,SAP, ERP, Oracle Database, Business Objects, Cognos Analytics, AWS, Spark, Visio, PeopleSoft, Big Query, Google Analytics

PROFESSIONAL EXPERIENCE

Confidential

BUSINESS ANALYST

Responsibilities:

Collected, aggregated and analyzed large amounts of data from various sources to perform analysis on the measures taken during recent pandemic.
Analyzed historical data, productivity, and current trends to identify risks and opportunities.
Analyzed Merchandising sales using SQL and Excel to enhance for next Fiscal Year.
Utilized Power BI to minimize the difference between Gross Demand Sales and Actual Shipped Sales to maximize profit.
Analyzed Quarterly Analysis utilizing Pivot Tables in Excel and Power BI for stakeholders and clients.
Developed dashboards for clients and stakeholders using Excel and Power BI analyzing top 10 items, catalogs on quarterly basis and also monthly basis based on Gross sales and Gross Units.
Maintained and Analyzed weekly reports projecting Gross Demand Report, Item Performance, Strategic Planning.

Technical Skills: Power BI, SQL, Excel, VLOOKUP, Pivot Tables

Confidential

DATA ANALYST

Responsibilities:

Collected, aggregated and analyzed large amounts of data from various sources to perform analysis on the measures taken during recent pandemic.
Analyzed qualitative and quantitative real time using data to identify trends and find answer for Covid-19 using Python and Excel.
Prepared reports and presentations using Tableau, Looker.
Balanced multiple projects and produced high-quality results in a deadline-driven environment
Executed Mini batch K-Means and K-Means algorithm on JSON and shape file and performed visualization techniques.
Successfully concluded that Mini batch K-Means computational time is less than normal K-Means because mini batch K means implementing itself in batches, hence taking less time to execute.
Deduced that clusters generated have decisive effect on execution time of algorithm amounting to average execution difference of 40 Ms.
Built a sentiment analyzer that checks whether tweets about a subject are negative or positive.
Used Twitter API to do the analysis on social media data.
Python library Text Blob was used for Natural language processing (NLP) task of sentiment analysis.
The analyzer displayed whether the tweets were positive, negative or neutral.
Identified demand patterns to recognize potential target market and improve existing market.
Investigated credits risk sources and suggestions to mitigate it.
Identified potential new products or services based on historical demands and patterns.
Identified demand patterns, potential market and customers using Tableau and aggregation techniques
Executed Random Forest Model to predict default and bad loans with 82.3% accuracy.
Analyzed rate of return, loss of every grade of loan in Excel with the help of Charts, Pivot Tables and VLOOKUP.
Analyzed raw data of IPL Cricket tournament for the year 2008-2016 to find the best performances of teams and players
Used Python to extract and clean dataset to eliminate redundancies and ensure integrity of data used for further analysis
Created data frames using Pandas and manipulate array using NumPy to optimize analysis by excluding irrelevant data
Developed recommendation system for team owners for better team selection in upcoming seasons based on performance

Technical Skills: Python, R, Tableau, Power BI, SQL, Looker, Regression Techniques, Forecasting, VLOOKUP, Pivot Tables

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