Shrikrushna Wagh
Summary
Senior Analyst | Software Engineer Bachelor's of Engineering in Computer Science and Engineering having 2.6 years of professional experience in IT.
Overview
2
2
years of professional experience
5
5
years of post-secondary education
5
5
Certifications
3
3
Languages
Work History
Data Analytics
Capgemini Technology Services Ltd
05.2021 - Current
- Achievements/Tasks o Received, cleaned, and prepped data from client using
- Python, SQL, and Excel to help data scientists build marketing mix models that resulted in a lift in ROI of 8 basis points
- Built data visualizations using SQL and Power BI for business KPIs that reduced manual reporting work by 10 hours weekly → Collaborated with product managers and analysts, gaining insight and growth in marketing aspects and writing documents based off user data
- Identified strategic marketing opportunity for client through detailed analysis with intern team, making recommendations that saved client over $10K in yearly campaign costs.
Data Analytics
Capgemini Technology Services Ltd
08.2020 - 05.2021
- Created visually impact Power BI dashboards to provide insight from the dashboard
- Mumbai, India in linkedin.com/in/shrikrushna-wagh-03a62a187
Education
Advanced Certification Programmed in Data Science -
IIIT
11.2021 - Current
Bachelors Of Engineering - undefined
G. H. Raisoni College Of Engineering
07.2016 - 05.2020
Skills
Reviews to be presented to business and IT usersBuilding, publishing customized interactive reports andDashboards using Power BlAnalyzed data and converted it into actionable insightsNagpurCoursesComputer Science AndEngineeringCGPA-89Data AnalysisData ManagementData CleaningData ScienceData VisualizationPython NumPy, Pandas, Matplotlib) Excel SQLPower BIMongoDB Critical ThinkingBig Data Analytics HTMLCSSJavaScriptTRAINING AND INTERNSHIPSWeb DevelopmentMATRIXHUB TECHNOLOGY SERVICES INDIALIMITEDTasks/AchievementsFront-end web developmentWordPress DevelopmentHTML, CSS, JavaScript and PHPClient DealingsPROJECTSExploratory Data Analysis: Credit DatasetThis case study aims to identify patterns which indicate if aClient has difficulty paying their installments which may beUsed for taking actions such as denying the loan, reducing theAmount of loan, lending (to risky applicants) at a higherInterest rate, etcAnalysis: RSVP Movies Case StudyThis case study aims to find various patterns in movie relaseTopmost actors, directors And recommend when movieShould be relased in which season, what should be theAverage duration using SQLLinear Regression Analysis: Bike Rental SharingIn this case study I used Multiple Linear Regression model forThe prediction of demand for shared bikes And whichVariables are contributing in our predictionLANGUAGESMarathiNative or Bilingual ProficiencyHindiFull Professional ProficiencyEnglishProfessional WorkingProficiency
Timeline
Advanced Certification Programmed in Data Science -
IIIT
11.2021 - Current
Data Analytics
Capgemini Technology Services Ltd
05.2021 - Current
Data Analytics
Capgemini Technology Services Ltd
08.2020 - 05.2021
Bachelors Of Engineering - undefined
G. H. Raisoni College Of Engineering
07.2016 - 05.2020
TRAINING AND INTERNSHIPS
Web Development
MATRIXHUB TECHNOLOGY SERVICES INDIA LIMITED
- Front-end web development
- WordPress Development
- HTML,CSS,JavaScript and PHP
- Client Dealings
PROJECTS
Exploratory Data Analysis: Credit Dataset
- This case study aims to identify patterns which indicate if a client has difficulty paying their installments which may be used for taking actions such as denying the loan, reducing the amount of loan, lending (to risky applicants) at a higher interest rate, etc.
Analysis: RSVP Movies Case Study
- This case study aims to find various patterns in movie release, topmost actors, directors. And recommend when movie should be released in which season , what should be the average duration using SQL.
Linear Regression Analysis: Bike Rental Sharing
- In this case study I used Multiple Linear Regression model for the prediction of demand for shared bikes. And which variables are contributing in our prediction.