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Click here or scroll down to respond to this candidateData Analyst Marketing Analyst Data Scientist Business Analyst Machine learning EngineerData Mining Data warehousing Agile Methodologies Business Process Modelling. Professional summary:to excel in roles that revolve around insightful data analysis and compelling data visualization. I bring a strong passion for data and a wealth of practical knowledge to the role. My debut to the world of data science was through the challenging root cause analysis for low user conversions on their new release of A: B test performed for a very top merchant in India, where I analyzed and found the root cause of their decline in the user conversions on the new release. Skilled in performing root causes analysis for Ad-hoc queries in R/python, Developing API fixes, AI/ML, Generative AI and proposing solutions for improvements with statistical grounds, EDA, Feature Engineering, Model building for business, automate data analysis in R/Python, SQL, BigQuery, MS Access, OLAP & OLTP Databases, building customized analytics dashboard using R/shiny, setting up insightful reports/Realtime alerts using R.Given my work experience, I've directly worked with merchants and closely with senior management on building merchant insightful reports, analytics for generic recon+settlement systems, building API's in R for data fixes, fast-tracked payment page release processes, ETL pipelines and dashboards. This experience has ignited me to possess a strong stakeholder management. Professional Experience:Data Science Industry Practicum Intern, Detroit 05/2024 08/2024 ASX Airspace Experience Technology Inc AeroNet. Documentation for Docker and implementation for Map tools in Docker. Assisted with analysis of communication data between ground station and aircraft to detect failure points. Developed tools for route planning in service of an eventual automated traffic management system Conducted and visualized radio map data for Lansing, including vehicle radio range analysis and visualization.Data Research Student Assistant: 01/2024-08/2024Wayne State University College of Engineering Detroit, United States Analyzed data to understand applicant demographics and implemented strategies on reaching as many applicants as possible implemented outreach programs to target a wider audience. Strategically analyzed applicant and student data to optimize outreach efforts, expanding program accessibility and diversity. Designed and executed surveys, questionnaires, strategically Orchestrated streamlined data collection processes, fostering collaboration across college departments and ensuring regulatory compliance.EMAIL AVAILABLE LinkedIn https://www.kaggle.com/brundashekar/codehttps://github.com/Brundashekar 248-739-3790 https://sites.google.com/view/brunda-shekar/home With over 6+ years of dedicated experience in Data analytics, Business Intelligence, ETL, Data Visualization, Data Governance, AWS Cloud, AI/ML,Generative AI and stakeholder management. I'm passionately driven Implemented advanced data management tools to glean actionable insights, driving informed program enhancements and strategic decision-making. Created flyers on Canva for organizing events to target more students for this program.Instructional Teaching Assistant: Python 08/2023 - 12/2023 Wayne State University College of Engineering Detroit, United States Served as a Teaching Assistant and Lab Instructor for "Introduction to Programming and Computation: Python BE 1600" course at Wayne State University under Professor Thaer Jayoussi. Guided students through lab assessments, providing instruction and support to enhance their programming skills. Evaluated and graded lab assessments and assignments, ensuring accurate and fair academic assessment. Data Analytics Product Management Intern, AAYM Detroit, United States 09/2022 - 09/2023 Utilized management tools like Asana, integrated with Microsoft Teams, and Signal Hire for effective project and communication management. Conducted qualitative customer research and maintained project plans, tracking dependencies and updating milestones.Data Analyst, Juspay Technologies Pvt Ltd Bengaluru 01/2019 - 05/2022 Root causing issues and implementing solutions to enhance revenue and success rates by 53%. EDA/Feature Engineering for Business: Performed Exploratory Data Analysis for Business on different products (payment page, UPI, Recon) in Bigquery/Python. Created tools using Jupyter notebooks to automate the initial phase of analysis, helped deliver the accurate results in half the time. Business Analysis: Executed root cause analysis for ad-hoc queries in R/python and proposing solutions for improvements in statistical grounds to improve user conversion for the merchant. Providing eye-catching insights for internal product teams (payment page, recon, upi) on improvising thee product and providing data sanity checks on funnels by bringing intelligence to the team. Real Time alerts: Setting up real-time alerts for internal product teams and merchants to proactively identify issues. Automate reports: Configuring insightful performance reports to merchants primarily to identify actionable to improve their success rate and get visibility. Setting up automated reports for Merchants as per the requirements in various formats (csv, excel, pdf, shiny rmarkdown) and sending insightful through various sources(slack, email, sftp). ETL's and Automating scripts: ETL Pipelines to transfer and clean data from OLTP databases like MYSQL, Postgres and load into OLAP data warehouse BigQuery, Clickhouse. Automated R scripts and APIs for data fixes: Build APIs for card BIN automation and other DB status mismatch data fixes. Spearheaded a team to build a generic recon+settlement system. Fast-tracked releases by automating release processes for the payment page. Build customized analytics dashboard using R/shiny /Grafana based on merchant's requirements. Attended various client calls to gather requirements and pain points, perform analysis and deliver the results in an intriguing fashion.Technical Product Analyst - Data Team 01/2019- 12/2019 Managed multiple teams with Data Governance Strategies with AAYM, focusing on global yoga awareness, and oversaw two critical system modules.Juspay Technologies Pvt Ltd BengaluruTechnical Product Analyst Intern 09/2018 - 12/2018 Juspay Technologies Pvt Ltd Bengaluru, India.Skills/Languages/Tools /Framework:Python Library numPy, SciPy, TensorFlow, Py Torch, Pandas, Matplotlib, scikit-learn, keras, scapy MachineLearningLinear/Logistic Regression, SVM, Random Forest, KNN, K-Means, Nave Bayes, Decision Tree, hugging face librariesAnalytics tools Business Intelligence, Merchant Insightful Reporting by R, Alteryx, Funnel Analytics. Data visualization high charts, Tabulae, Alteryx, Power BI, ggplot Data Crunching R/ Google Big Query, Market Analytics, Automating scripts in R, API fixes in R ComputationalIntelligenceMachine learning methods to solve complex analytics problems and develop decision support systems, project-centric approach for Intelligent Analytics. DevOps &DeploymentAWS Azure DevOps and docker build for Map tool, API fixes in R & deployment. Operating System MacOS, Ubuntu, Linux.DataVisualization &BITableau, Microsoft Power BI, QLIK Sense, High charts Databases MS SQL, Mango DB, MS Access, Google Big Query, Postgres, Click house, OLAP & OLTP Designing/ppttoolsCanva, MS ExcelTools Hugging face, Databricks, Power BI, Synapse, MS SQL Server (SSMS, SSIS), MS Visual Studio, InteliJ IDEA, MS Office.CloudTechnologyAmazon Web Services (AWS), Microsoft Azure.Methodology Agile, Scrum, Waterfall, Stakeholder Management, Business Process Modelling. Version Control Git, bitbucket, JIRAEducation:Master of Science: Data Science and Business Analytics, Anticipated 12/2024 Wayne State University 4 GPA - Detroit, MIPG Diploma in Data Science and Business Analytics, 11/2022 IIIT Bangalore PG Diploma in Data Science Bengaluru Bachelor of Science: Computer Science, 08/2018M.S. Ramaiah University of Applied Sciences Bengaluru COURSE PROJECTS:1. California Housing Price Prediction: -Developed a predictive model to estimatemedian house values in California.Created a machine learning model to predicthousing prices in various California districtsbased on multiple features. Analyzed housingdata to aid homebuyers, sellers, and realestate professionals in property valuation,investment decisions, and understandingmarket trends.2.Brain tumour classification:Developed a robust machine learning model for brain tumor classification using MRI images.Leveraging deep learning techniques, MLP to classify brain images into tumor/non tumor classes.Used Transfer learning model, Imagenet 21K pre-trained model.Added 2 dense layers to tweak as binary classifier. 3.DSE6000: Preformed exploratory Chronicdisease analysis in USA by building thedashboard, and representing insights withdifferent plots like correlation heatmap,count of each topic in theDataset. Displayed mortalitytrends/hospitalization trends with beautifulvisualizations and found insights. Made aninitial analysis of data for Applied MLpredictive analytics by building a suitableregression model to do some predictions byselecting suitable independent variables.4. DSB6000: Project on how organizations like VBCboard can leverage data science and analytics to gain competitive advantage and how to use thedata to align with a company's mission & goals.Presentation on how VBCaddresses each of the 9 elements of the data science strategy Culture,. Program Management and Strategic Roadmap.. Highlighted the process of extracting business value and impact, determine5. DSA6000: Classification ModelBenchmarking:Conducted a comparison of classificationmodels using a set of 20 Datasets. Theproject comprised two distinct phases: in thefirst phase, we utilized default predictors,while in the second phase, models wereconstructed through forward model selectionfrom various datasets.KAGGLE PROJECTS: Machine Translation: Task of automaticallytranslating text or speech from English toFrench. California Housing Dataset: -Tsne, uMAP, F-test ANOVA, PCA. Customer Churn Analysis: Created a logisticregression model to predict the category ofchurned customers in Telecom Industry. Lead Scoring Case Study [Model Building]Kaggle: Built a logistic regression model toassign a lead score between 0 & 100 to each ofthe leads which can be used by the company totarget potential leads. Bike Sharing Linear Regression ModelKaggle: Created an ML Model using linearregression to predict the factors affecting bikedemand. IMDB EDA - Case Study Kaggle: Performedan EDA on IMDB Dataset and found someinteresting insights into these movies, votersusing Jupyter notebooks in Python. |
