Data Analyst

DAWNA GRACE RAJ SATHIA

Boston, MA-***** 781-***-**** ******.*@*****.***.*** https://www.linkedin.com/in/dawna-grace-raj-sathia/ Education

Northeastern University, Boston, MA Aug 2019

Master of Science in Information Systems

Anna University, Chennai, TN, India May 2013

Bachelor of Engineering in Electronics and Communication Engineering Technical Skills

Databases : MySQL, MS SQL Server, Oracle 11g, PostgreSQL, Redshift, MongoDB, DynamoDB Languages & tools : SQL, Python, Tableau, Qlik Sense, Qlik View, Power BI, Excel (Pivot, VLOOKUP) Data Integration : Talend Open Studio (Big Data Integration), SSIS, Alteryx, Informatica Libraries : Pandas, NumPy, Scikit-Learn, StatsModels, Matplotlib, Bokeh, SciPy, Plotly Cloud Technologies : EC2, S3, IAM, CloudWatch, MS Azure, Google Cloud Platform Other Tools : Collibra, Google Analytics, Toad Data Modeler, Jenkins, Docker, JIRA, Confluence, Git Experience

Fidelity Investments, Boston, USA-- Data Analyst (Co-op) Jul 2018 – Dec 2018

• Validated terabytes of data, performed data quality management by creating optimized PostgreSQL nested queries using joins, indexing, views and reduced per query execution time by 2.5 mins

• Designed interactive dashboards in Qlik Sense and Qlik View to monitor performance of SAS and python models

• Partnered with Data Scientists in agile environment to develop Model Evaluation utility to capture model scores

• Identified anomalies in large datasets and implemented best anomaly detection algorithm that increased data quality by 95%

• Outlined and formulated KPI metrics for multiple models to govern model performance across all model families

• Automated in-production Model Metadata from Atlassian Confluence to PostgreSQL Database with REST API services and diminished manual data entry

Cognizant Technology Solutions, Chennai, India-- Associate Data Quality Analyst Jan 2014 – Aug 2017

• Performed ETL by extracting the data from files by Unix scripting, transformed and loaded data into Oracle database

• Created and executed complex advanced SQL queries for testing the data quality of multiple backend applications

• Conserved 90% of project resources by developing PL/SQL statements, Stored Procedures and maximized reusability

• Delivered Analysis & Insights report to end-users stakeholders for evaluating production release performance using Tableau

• Spearheaded a team of 5 and achieved ‘Project of the year’ award for innovation, cost saving, quality of workmanship

• Programmed addressing areas including database impacts, software scenarios, regression testing, negative testing, performance testing, bug retest, usability and documentation Amazon Development Center, Chennai, India-- Quality Analyst Aug 2013 – Jan 2014

• Developed and Executed test scenarios, test cases to perform mobile testing by downloading builds from Jenkins

• Tested Amazon Kindle application on a variety of Operating system platforms and documented test logs using MS Excel

• Automated manually run test cases to a python-based robot framework which reduced manual effort by 75%, saved execution time by 9 mins per testcase and eventually yielded profit of $ 7,000 per week

• Formulated VLOOKUP to search accomplished test data from multiple workbooks and improved process time by 15 mins Projects

Fintech Hiring trends in the largest banks around United States Spring 2019

• Scraped large data from Fintech articles with BeautifulSoup, Selenium python libraries and performed data cleaning, Exploratory Data Analysis to get insights and patterns of keywords related to Fintech Big Data, AI, Blockchain

• Extracted job applications from top 24 US banks and identified Fintech trends in each job by feature engineering

• Visualized and drew insights on job market, hiring trends and most widely required technology with tools

• Reported analysis, key findings through Google Claat reporting tool and pipelined end to end process Predict Interest Rates of Lending Club Data Spring 2019

• Researched on various clients to analyze their credit history with the help of graphs & charts provided by lending club

• Prepared data by performing data cleaning, exploratory data analysis, manual feature engineering, feature tools

• Developed machine learning models Linear regression, Random Forest and Neural Networks models along with k-fold cross validation to predict interest rates and chose Neural Networks as best model with MAPE score of 23%

• Performed AutoML (TPOT, AutoSKLearn, H2o.ai) and obtained Linear Regression as best model with R square of 88.07% Data Integration and Visualization Spring 2018

• Extensively used ETL methodology and designed Star Schema Dimensional model for retail store database of 48M rows

• Devised Data Profiling, Data Migration and loaded data into data warehouse using Talend Open Studio and SSIS

• Built interactive dashboards using Tableau, PowerBI and Qlik to convey stories of retail sales and customer segmentation

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