Data Analyst Python

HIRAL RATHOD

adifjr@r.postjobfree.com 617-***-**** linkedin.com/in/hiral-rathod/ https://github.com/hiralrathod Technical professional with 2 years of experience in software engineering and data analytics. Blend of both domains provide me an extra edge in solving business problems from a technical standpoint. Seeking roles around analytics that would foster my career growth and help to advance a progressive employer

EDUCATION

Northeastern University, USA. Sep 2018-Jul 2020

Masters in Analytics. GPA: 3.7/4.0

Vice President – Northeastern University Graduate Women Coders Club University of Mumbai, India Aug 2013-May 2017

Bachelor of Engineering in Information Technology. GPA: 7.13/10 TECHNICAL SKILLS

Languages & Cloud: SQL, Python, R, NoSQL, AWS (S3, EC2, Redshift, Quicksight), Google Cloud Platform (GCP) Databases & Version Control: SQL Server, MySQL, SQLite, PostgreSQL, MongoDB, Git Business Intelligence Tools: Talend, Power BI, Tableau, Google Data Studio (GDS), Excel Big Data and other tools: Hadoop, Spark, Elasticsearch, Logstash, Kibana, Confluence, JIRA, G Suite, Google Analytics PROFESSIONAL EXPERIENCE

Data Analyst [JerseySTEM NGO, NJ, USA] Aug 2020-Present

• Performed root cause analysis using Confluence reports on employee onboarding and offboarding data for efficient data mapping

• Designed dashboards using GDS to capture volunteer’s data metric to outline volunteer retention and recruiting strategies

• Deployed data management workflow using JIRA, automated a fresh data collection process that reduced 20-man hours per month Technical Business Analyst [Charles River Development, MA, USA] Jul 2019-Dec 2019

• Maximized product performance by reducing 24% of system parameters using SQL scripts & presented a dashboard using Power BI to senior management

• Improved user experience by incorporating business development strategy for company’s investment management platform to overcome procedures affecting database management

• Optimize performance tuning for effective database querying by coordinating with QA and Automation team to validate test cases

• Integrated Elasticsearch to monitor log & app usage to understand user sessions, generated Kibana reports on exceptions occurred Software Engineer [Laminaar Aviation Infotech Pvt Ltd, MH, India] Sep 2017-Jul 2018

• Succeeded in improving average response time of Aviation resource management system’s web app built on MVC from 30s to 12s

• Employed RESTful APIs using C# that served data to our JavaScript UI based on dynamically chosen user inputs

• Queried a mechanism to maintain logs using SQL triggers & maintained project related user manuals using Tableau

• Implementing agile methodology in phases of SDLC and found solutions to complex technical issues by implementing troubleshooting strategies

PROJECTS

Capstone: J Crew [Tableau, Python, Talend] Jun 2020-July 2020

• Formulated marketing strategies using python for better sales and profits of company at various locations on J Crew’s sponsored dataset

• Engineered ETL pipeline through Talend to map zip code level data collected using web scrapping to original dataset and designed dashboards using Tableau to understand buyer’s shopping patterns

• Built multi linear regression & market segmentation to make future revenue predictions with 63% accuracy Architecture for a Company [AWS cloud architecting, SQL] Mar 2020-Apr 2020

• Assembled a robust architecture on AWS to deploy a simple Web Application, previously hosted on legacy architecture to efficiently reduce cost, downtime, latency, and query time

• Utilized CloudWatch to detect anomalous behavior in the environment, Autoscaling Groups to optimize availability, Security Groups to ensure maximum security and ELB to distribute traffic across multiple Availability Zones

• Created a centralized database using MySQL RDS instance & connected it through process environment using AWS SDK’s NLP with disaster tweets [Python, NLP, Predictive Analytics] Jan 2020-Feb 2020

• Classified tweets into disaster and non-disaster categories using Recurrent Neural Networks

• Performed EDA using python libraries like matplotlib & Seaborn to understand distribution of target variables

• Preprocessed data using Regular expression to create a dictionary utilized by model and tuned hyper parameters to achieve maximum accuracy of 76%

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