Python Data Analyst

Susmitha Vegesna

***************@*****.***

408-***-****

SUMMARY

·Expertise in Machine Learning / Deep Learning Algorithms and Python Full-Stack Development.

·Hands-on experience on Python libraries like Numpy, Pandas, Matplotlib, Seaborn, NLTK, Sci-kit learning and SciPy.

·Experienced in Project lifecycle - Requirement analysis, Data wrangling, Model creation/Training, Model Evaluation, Visualization.

·Implemented Machine learning models like logistic regression, decision trees, random forest.

·Created neural networks to perform text analytics while utilizing natural language processing concepts like tokenization, case conversion, word replacement, lemmatizing, stemming.

·Worked on Python Full Stack frameworks like Django and Flask.

·Experienced in agile development framework - Scrum.

·Worked on cloud platforms like Floydhub, Azure Cloud/ Azure ML.

WORK EXPERIENCE

Professional

Software Engineer (Consultant), Google 3/2019-present

Sunnyvale, California

·Analyzed Logs to identify the root cause of bugs in android applications.

·Using Plx Scripts built custom dashboards to visualize reported issues and their status.

·Automated android applications user feedback issue reporting process.

·Created Python script using object oriented design Principles to build infrastructure for testing environment.

·Performed compatibility analysis of in-house and third party applications on chrome books - Pixelbook, Pixel Slate, Pixel Go in Canary, dev and beta channels.

Machine Learning Consultant, SST Finance 09/2016-11/2018

Remote

·Assisted with creating and training loan prediction machine learning model to validate customer eligibility.

·Preprocessed data to handle missing values and encode categorical features.

·Utilized logistics regression, random forest classifier and decision tree models to optimize results.

·Supported with hyper parameters tuning and used F1 score, confusion matrix metrics to evaluate the models.

·Helped with identifying and developing valuable new sources of data collection, collaborated with product team to ensure successful integration.

Fundraising Volunteer, American Redcross 03/2016 - 10/2018

Milwaukee, Wisconsin

·Actively participated in conducting Volunteer Appreciation events and planning Brave Heart event.

·Searched and finalized venues, caterers, menus and gifts for multiple Volunteer Appreciation Events.

·Contributed in identifying Heroes in Southeast Wisconsin Chapter and having them nominated for Brave Hearts.

Data Analyst, Kroger 07/2012 – 01/2015

Cincinnati, Ohio

·Mechanized Ad hoc Reporting and Issue Support jobs that saved 30 hours of resource time per month.

·Automated a reporting tool that reduced the hours spent on an audit from 3 hours to 10 min.

·Generated complex SQL queries against large relational databases to pull history of employees.

·Initiated the practice of documenting the work among the team.

·Instrumental in creating environment baseline and batch cycles for payroll yearend testing.

·Assisted with stake holder requirements analysis, scheduling, problem solving, prioritizing, decision making, time management and, process improvement.

·Mentored junior programmers in programming methodologies and best practices.

Web developer Intern, SST Finance 04/2011 – 06/2012

India

·Customized company website interfaces with HTML, CSS and JavaScript technologies.

·Coordinated to finalize designs and confirm requirements.

·Provided methodologies for website development and updated database design using SQL.

·Kept abreast of emerging technologies, software and trends and applied them to projects.

Projects

Text Summarizer

• Created a Recurrent Neural Network on 50,000 food reviews to generate a review summarizer that summarizes given review in 4 to 13 word sentence.

• Performed tokenization, case conversion, word replacement, lemmatizing, stemming on the data using NLTK.

• Built the Encoder Decoder seq2seq model with Long Short Term Memory (LSTM) cells using TensorFlow library .

• Used Learning rate decay and early stopping methods to train the model effectively.

Image Classifier

•Built a Convolutional Neural Network over CIFAR-10 data set that identifies images.

•Used python libraries like NumPy, Pickle for preparing data and calculations.

•Utilized TensorFlow library for creating and training the CNNs.

•Utilized Floyd hub for computational power.

SKILLSET

Languages: : Python, Django, Flask, Java, JavaScript, HTML, CSS, Linux, android, SQL

Statistical Analysis & Machine Learning : Neural Networks, Classification, Regression, Random Forest, Decision trees

Frameworks/Libraries : Tensorflow, Scikitlearn, Sklearn, Pandas, Numpy, Pick le, .Matplotlib

Databases : IBM DB2, MySQL, SQLite

EDUCATION

·M.S. in Information Technology 08/2016-12/2018

GPA: 3.83

Coursework: Artificial Intelligence, Database management systems, Web Systems & Technologies, Data Security & Information Assurance.

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