Nidhi Shah

adcmic@r.postjobfree.com 857-***-**** Boston, MA linkedin.com/in/nidhishah6 github.com/nidhi15 SUMMARY

Self-driven and result-oriented data professional with a strong will to succeed and deliver excellence through technology innovation around data analysis, advanced analytics, and machine learning in the world where data makes a difference. EDUCATION

Northeastern University, Boston, MA Apr 2020

Master of Professional Studies in Analytics, GPA: 3.93 Concentration: Statistical Analysis, Predictive Analytics, Data Mining, Data Management Teaching Assistant for Communication/Visualization for Data Analytics course Rajiv Gandhi Prodyogiki Vishwavidyalaya, Indore (MP), India Jul 2012 Bachelor of Engineering in Computer Science, GPA: 3.75 CERTIFICATIONS

AWS Certified Cloud Practitioner Feb 2020

PROFESSIONAL EXPERIENCE

Qlik Tech Inc., Boston, USA Jul 2019 – Dec 2019

Data Catalyst Co-op, Enterprise Data Management

● Engineered an Artificial Intelligence Solution to identify and tag data in big data sets for Qlik’s Data Catalyst (QDC) commercial product, enabling the build of a GDPR and CCPR compliance solution that eliminates 75% of manual data governance effort

● Developed a business glossary application and built the first 250 business terms for Qlik customers, leveraging the AI solution. This prototype became a key part of the standard Qlik selling solution that drove the increase in sales by 25% in one quarter after launch

● Worked with Qlik Engineering to influence the development of the Qlik Cognitive Engine using NLP and augmented intelligence

● Created visually impactful Qlik Sense dashboards for Admin reports. Extracted and analyzed monthly trends to identify key metrics Parkar Consulting & Labs, Pune, India (Clients: ScienceLogic, Neustar) Apr 2016 – Jun 2018 Senior Technical Associate, ScienceLogic Certified Professional, Awarded “Above and Beyond”

● Fixed critical issues for major customers like Cisco and CBTS, automated test scripts in Python reducing backlog count to 120 from 400

● Demonstrated seasonal analysis approach to forecast the data by analyzing earlier data log entries for NEMP project

● Enhanced new features like “Historical Graph Comparison” and “Purge Maintenance Window” in Neustar’s web performance tool WebMetrics for Apple and AT&T enhancing the functionality usage by 70%

● Migrated Webmetrics application code into Web Performance Monitoring application using Django framework improving the migration performance by 80% and impacting more than 200 customers Sears IT & Management Services India Pvt Ltd, Pune, India (Client: Sears Holdings) Jul 2012 – Mar 2016 Technical Associate, Awarded “Applause Award”

● Worked for the Legacy Mainframe elimination program by converting jobs to distributed architecture and setting up advanced Monitoring to meet Production SLAs, eliminating more than 500 mainframe application MIPS (million instructions per second)

● Processed a large amount of data in HDFS using Shell scripting, Sqoop, Pig, Hive and analyzed the Mainframe LLD business requirements to optimize the logical flow of the application

● Performed detailed analysis for client’s supply chain model including Pricing, Best Vendor Pack (BVP) and Open Item (Inventory) module

● Committed to automate routine processes by writing UNIX shell scripts to reduce manual effort by 80% TECHNICAL SKILLS

Programming Languages Python (Pandas, NumPy, SciPy), R (ggplot2, tidyverse, etc.), Shell Scripting Data Technologies Quantitative research methods, Regression Analysis, Data mining and Data QA, Pattern and Trend Identification, Data Warehousing, Data management, Statistics and Probability Database MySQL, PostgreSQL, SQL

Big-Data & Cloud Ecosystem Hadoop, AWS, Databricks, Pig, Sqoop, Hive Tools Tableau, MS Excel (VLOOKUP, Pivot Table), Qlik Sense, R Shiny, RabbitMQ, Crontab, Control-M (Scheduler) ACADEMIC PROJECTS

Prediction for Costa Rican Household Poverty Level Oct 2019

● Performed analysis to recognize the family units that have the most serious requirement for social welfare assistance using Stepwise Regression and Ordinal Logistic Regression

● Optimized the model using Extreme Gradient Boosting method which resulted in 86% accuracy Data Integration and Visualization for Boston’s Property Assessment May 2019

● Interpreted Boston’s real estate data with the help of exploratory analysis, performed data cleaning, outlier analysis for 60000+ observations and 15 attributes using R programming libraries tidyverse, simplyEDA.

● Examined trends and relations between attributes by creating visuals, graphs and dashboards in Tableau for forecasting the best place to live in Boston. Results showed Fenway as the best place to live in Boston

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