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Data Analyst Python

Location:
Norman, OK
Posted:
September 08, 2020

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Resume:

Meera Bankar, Data Science Graduate

+1-405-***-****, adfxer@r.postjobfree.com

LINKS Linkedin, Github

EMPLOYMENT HISTORY

Sep 2012 — Jul 2018 ETL Engineer & Data Analyst, Synechron Technologies Pune, India Data analysis with Tableau, ETL process implementation with SSIS & Informatica. The role involved SQL scripting, data analysis, data processing, maintaining data integrity and verifying pipeline stability, data validation of ETL jobs for clients Verizon, ATT, TMO, MetroPCS in the insurance domain (Main client: Asurion). Feb 2019 — Jul 2020 Data Scientist (Graduate Research Asst.), OU (ODOT) Norman, USA SAFE-T is a state-level collision data analysis application to improve Oklahoma state highways. The role involved predictive modeling with machine learning algorithms in Python to predict the collisions in Oklahoma state. Also, collision data analysis for all sections in Oklahoma state, get insights and provide it to the highway safety authority at ODOT(Oklahoma Dept. of Transportation) to make decisions to reduce the collisions, and UI development with PHP and MySQL.

Aug 2020 — Dec 2020 Data Science Intern, Paycom Oklahoma city, USA Implementation of predictive models from scratch with different machine learning algorithms in Python and R. It involves data gathering, data processing, model building, model evaluation and rating. Implemented models will be used in various payroll processes in Paycom. EDUCATION

Jul 2008 — Jul 2012 BE(Computer Science), S.R.M.T. University Nanded, India Aug 2018 — Dec 2020 MS (Data Science and Analytics), University of Oklahoma Oklahoma, USA PROJE CT E X PE RIE NCE

Sep 2018 — Dec 2020 Machine learning predictive model projects Norman, Oklahoma, USA Amazon Toy Recommendation System: A recommendation system implemented using the Apriori algorithm, K-means & DBSCAN clustering on amazon customer purchase history data. The new feature in this is that system recommends frequently bought together products as well as similar products based on price/ rating/ category of products. The model is 87% accurate.

Abnormality Detection from X-ray images: Implemented a machine learning predictive model (86% accurate) in Python TensorFlow to identify abnormality of different body parts form x-ray images using CNN, ANN with functional API approach.

Collision and collision severity prediction (ODOT): Built a predictive model(94% accurate) to predict collision and collision severity in Oklahoma state to improve Oklahoma roadways. Model is built with Random Forest, SVM, Neural Network and KNN classifier. Bank Marketing: (Paycom SEP work) Keeping the goal of marketing in mind, the model(91% accurate) built predicts if customers will subscribe to a finance product based on campaign data of Portuguese bank. Model is built with RandomForest, XGBoost in python and is evaluated with ROC, accuracy, F1- score. Fraud Transaction Detection: Model(89% accuracy) to predict fraud transactions based on customers’ transaction history, purchase patterns. Model is built with SVM, decision tree, ANN, Random Forest and is evaluated with F1-score, accuracy.

Home Credit Risk: Model(90% accurate) to predict customers who can repay loans using data in Home Credit bank. It's built with decision trees, random forest, deep learning, SVM in R, Python and evaluated with ROC, F1 score, cumulative gains chart metrics. It is used to get creditworthy customers before providing loans or cards. SKILLS Python, R, SQL, MySQL, C, C#,

Java, PHP, HTML, JavaScript

Data Science: Predictive

modeling, Machine Learning,

Data Wrangling, Data Processing,

Data Visualization, NLP

Tableau, PowerBI, SSIS,

Informatica, GIT, JIRA

Deep Learning(CNN, RNN),

Text Analytics,Statistics,

Tensorflow, Keras, Dataiku

JIRA, SDLC, STLC, Agile

Scrum, Team Work

ACCOMPLISHMENTS

- Maintained a 97% customer satisfaction and quality work rating throughout my tenure at Synechron

- Managed and delivered projects individually with full client satisfaction under guidance of Manager

- Converted client requirements to easily accessible and understandable doc format for one of the projects I worked on, which was appreciated and used by clients along with team and project coordinators. It helped to speed up the overall development process.

-Created a training manual for a project from scratch and led training sessions for new team members

- Delivered a complex project code in a short period of time

- Received Employee of the month award for delivering a critical release with product quality

- Received Spot ward for solving a complex problem which was an impediment for a third team.

- Received Surpass award for a good performance and consistent work throughout the year



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