Data Analyst Engineer

Pratiksha Sawant

San Jose, CA ***** +1-617-***-****

adkckr@r.postjobfree.com https://www.linkedin.com/in/pratikshas5/ https://github.com/pratiksha-sawant CAREER SUMMARY

An organized, meticulous professional with a master’s degree in Information Systems and four years of industry experience in the field of data analysis and backend/software engineering in Banking/Finance and Sales Operations. Strong analytical, reporting, data mining, data profiling and data visualization skills. Fundamental knowledge of statistics and machine learning models. Ability to work creatively and collaboratively in a problem-solving and fast-paced environment. EDUCATION

Master’s in Information Systems - Northeastern University, Boston, MA Sep 2018 - Aug 2020 Achievements: Best All Beginner Team Hack in TechTogether Boston Hackathon 2020 as a machine learning engineer Bachelor’s in Computer Engineering - University of Mumbai, India Aug 2010 - Jul 2014 Achievements: Stood 1st in the Department of Computer Engineering in College SKILLS

Languages Python, SQL, T-SQL, C++, PL/SQL, Java, HTML5, CSS Databases Microsoft SQL Server, MySQL, Sybase, Oracle 11g, MongoDB ETL Tableau Prep, SSIS, Talend Open Studio, Power Query, Alteryx, Apache Airflow Cloud Technologies S3, EC2, Kinesis Data Stream, Kinesis Data Firehose, SageMaker, Redshift, Azure ML Databases Microsoft SQL Server, MySQL, Oracle 11g, Sybase Data Visualization Tableau, PowerBI, matplotlib

Data Analysis & ML scikit-learn, XGBoost, pandas, NumPy, Excel, DAX Business Tools GitHub, SVN Tortoise, JIRA, Microsoft Office Suite (Excel, Outlook, Teams, PowerPoint, Word) WORK EXPERIENCE

The Ventilator Project – Data Analyst Intern – Sales Operations Oct 2020 – Till Date

• Built an interactive dashboard on Tableau for B2B reports highlighting the global ventilator demand for COVID-19 patients

• Identifying the leads for product sales by generating a report with details of potential buyer/client by using SQL queries WEX Inc, Portland, Maine - Business Intelligence Analyst Intern Sep 2019 - Dec 2019

• Created ETL data workflows on Tableau Prep to integrate, transform and store the data on MySQL database

• Automated the data collection by 80% by reading JSON response from API service using Python (pandas & Numpy)

• Enhanced KPI, revenue, and quality assurance analysis by 60% by creating interactive dashboards in Tableau

• Forecasted revenue outcomes with time series analysis on the transactional records for different business domains Syntel Private Limited, Mumbai, India – Associate Consultant (Data Analyst) Jan 2016 - Jul 2018

• Populated analytical reports and conducted data integrity, quality testing by extensive use of SQL queries

• Created demonstrative visualizations for financial analysis by using functions, pivot tables & charts in Excel

• Analyzed and tracked the performance growth of internal teams by creating interactive dashboards in Power BI

• Analyzed the data anomalies by performing root cause analysis of the issue and proposed solutions for production issues

• Collaborated with subject matter experts to conceptualize system design, leadership team, and other cross-functional teams to ensure scalability and smooth coordination amongst stakeholders for overseas clients

• Tuned performance of a web reporting tool by 25% with query optimization in stored procedures for data retrieval Syntel Private Limited, Pune, India – Associate Consultant (Software Engineer) Sep 2014 -Dec 2015

• Expedited the data retrieval by 30% using T-SQL by implementing stored procedures, views, and functions

• Enhanced the stand-alone application functionality by 40% on implementing back-end business logic in C++ ACADEMIC PROJECTS

Email Marketing System (Technologies: Azure ML, Flask, Power BI, Python, API, Heroku) May 2019 - Aug 2019 A web-based recommendation engine (RESTful API) to email movie recommendations to user and performed customer segmentation analytics, user activity analytics, email response analytics with embedded interactive dashboards. Song Mood Analyzer (Technologies: Scikit-Learn, Python, Flask, Heroku) Mar 2019 - Apr 2019 Web based supervised machine learning model with 80% accuracy to translate and classify songs by analyzing the sentiments. Models Evaluated: Logistic Regression, Naïve Bayes, Random Forest Lending Club Loan Data Analysis (Technologies: Airflow, Python, Scikit-Learn) Jan 2019 - Feb 2019 Automated data collection, cleaning, and feature engineering by creating a pipeline, predicted interest rates with Linear Regression Model (Accuracy: 97.3%) and classified risky or non-risky loans with XGBoost (Accuracy: 96.2%)

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