Medha Mallampati

Phone: 848-***-****

Email: ad2m0v@r.postjobfree.com

LinkedIn Profile: https://www.linkedin.com/in/medha-m-690b111a3/

EDUCATION

M.S. Health Informatics

School of Health Professions, Rutgers University

GPA: 3.975

Piscataway, NJ

September 2021 – May 2023

B.A., Rutgers University

Major: Biomathematics

Minor: Psychology

New Brunswick, NJ

May 2021

ABOUT

Actively seeking an entry level position in Data Science or Python Developer. I have experience in Data Science analytics utilizing programming tools such as Python and Python libraries (pandas, NumPy, Matplotlib, SciPy), SAS, and Machine Learning prediction techniques. In addition to programming tools, I have completed academic coursework and projects using MySQL DBMS and SQL. I have added R programming for data science to my knowledge base as well. I have a good grasp on analytical concepts, logical abilities such as analyzing large data sets, processing and cleansing data sets to maintain meaningful information, and making decisive decisions based on required information.

I thrive in a team environment but can also productively work independently. My flexibility and resiliency allow me to finish my work within the set deadlines. My enthusiasm for new knowledge keeps me up-to-date with the growing field of data science and its practices.

ACADEMIC PROJECTS

Machine Learning Project: Predicting if Income of Adults Exceeds $50k

Completed ML project ‘Census Income’ as part of my Machine Learning course curriculum.

The objective of this project is as follows:

Determine the best model in predicting whether or not a person has an income that exceeds $50K per year dependent on various factors.

Utilize ML techniques, advanced python tools and libraries (NumPy, pandas, SciPy, Matplotlib, scikit-learn) to analyze data extracted from the 1994 US Census database.

oData download and preparation.

oData Cleaning

pre-processing and feature selection

oSplit the training and testing datasets

Generate and compare various models performed based on data trends to determine the best predictor method

Generate data visualization charts for performed classification methods using visualization tools

oPlotted ROC curves to further evaluate the models

oCreated a bar chart for visual comparison of prediction scores

Conclusive Report:

The machine learning classification model that had performed the best in determining whether or not an individual's income exceeds $50k per year was the SVC RBF kernel classification combined with RFE.

Python Projects: Daily Activity Fitness Tracker

Completed python project ‘Daily Activity Fitness Tracker’ as part of my advanced python course ‘Data Science Programming’ curriculum. The objective of this project is as follows:

Utilize advanced python tools and libraries (Numpy, Panda, Matplotlib, Scipy) to analyze Activity data.

oData download, cleaning, and preparation.

oJoin multiple dataset tables

oAdd new columns to merged dataset

oRun statistical analysis tests

Generate various analytical reports to show:

oList Daily Summary data

oList average Calories, Step Total, Activity Minutes, and Activity Distance by Id

oDisplay Statistics of the Total criteria columns in Activity dataset

oList the Correlation between Step Total and Calories by Id

oPerform Linear Regression to analyze if Calories is impacted by Total Active Distance and Total Active Minutes

oRun a t-test to see if the mean of Step Total is equal to the recommended step total 10,000

Generate data visualization charts for the above reports using visualization tools.

Generated reports and charts for analysis as shown below:

Reported Daily Summary data making it easier to view at a glance the necessary data for the individuals daily report, all related to the days activity total.

Reported and analyzed individuals overall average activity intensity breakdown.

Reported the overall statistics of the individuals daily total data. This allowed me to see who was the most active, who was the least active, what their max/min calorie expenditure was and overall average.

Reported the correlation values for each individual, showing who had the highest correlation between total steps and calories. Displayed graph charts and line charts to analyze visually the individual’s with the highest/lowest correlation between total steps and calories.

Performed Linear Regression to analyze if Calories is impacted by Total Active Distance and Total Active Minutes.

Performed statistical testing, One sample t-test, on if the mean of Step Total is equal to the recommended step total 10,000.

MySQL Project: ABC Pharmacy Drug Dispensing and Tracking System

Completed project as part of my MySQL DBMS course curriculum. The objective of this project is to demonstrate the following:

Database design using visualization tools

oCreated an ER diagram to visualize relations between data objects

Database tables

oCreated tables (10)

Pharmacy, Drug Manufacturer, Doctor, Patients, Drugs, Pharmacist, Prescription, Prescription Items, Orders, Order Items

oData loading (hypothetical data self-generated)

oDefined relationships using foreign/primary/composite keys

Generated reports and charts for analysis as shown below:

Generated a list of the pharmacists working in the pharmacy ABCPharm displaying the pharmacy id, pharmacy name, pharmacist name, pharmacist license number, and phone number.

Generated a list of patients by their primary doctor where the report displayed the doctor’s name, doctor specialty, doctor phone number, patient name, patient gender, patient dob, and patient phone number.

Reported pharmacy drug supplier and their on-hand inventory, displaying the pharmacy name, drug supplier, drug id, batch number, drug name, type, manufacturing date, expiration date, and on-hand drug quantity.

Listed the patient’s prescription with the provided drug id and prescribed dosage given by their primary doctor on the date visited.

Listed the pharmacy orders and extended amount by date. Displayed in the report the order id, order item line number, order item drug id, order quantity, price, patient name, patient phone number, and pharmacist name.

Generated patients’ prescription order total cost provided by the pharmacist dispensing the prescribed drugs.

Tracking Drug Dispense information to patient and doctor by the drug manufacturer, drug name, the batch number, manufactured date, and expiration date.

oAt any time, this system can track the drug from drug supplier to the end patient, including the doctor who prescribed, as well as the pharmacist who provided dispensing services.

Displayed database max functionality by deleting row in table doctor.

oIn case of recalls, side-effects, supply shortage, etc., the tracking system will quickly identify the entire supply chain and alert those affected.

SAS Project: Assessing the Effectiveness in Drug A on Fasting Sugar Levels

As part of my SAS course curriculum, a study was conducted to determine whether Drug A helps to reduce fasting sugar levels. There are 3400 patients enrolled for this study and the fasting sugar levels were taken before and after consuming Drug A at a certain time interval. The objectives of this project are as follows:

To identify patients with blood sugar levels between 40 – 600 if there is a difference between before and after taking Drug A in blood sugar levels. If so, was that difference a significant decrease in blood sugar levels?

Is there a difference in after blood sugar levels between the age groups?

Similarly, is there is a difference in after blood sugar levels between states?

Is there an interaction effect for age group and state?

Is length of stay correlated to initial sugar levels and after sugar levels?

Created and sorted datasets, eliminated extreme values, merged data, and added new data columns. Ran statistical analysis tests and plotted data visualization charts.

I have completed the following courses as part of my M.S. curriculum:

Data Science using Advanced Python with Library Packages NumPy, pandas, Matplotlib, seaborn, & SciPy.

SAS v9.4 Programming to perform statistical analysis and reporting on data sets and generate data visualization charts.

Machine Learning techniques using Advanced Python with Library Packages to build a model based on training data in order to make predictions or decisions. Machine Learning techniques used throughout the course included regression, log-regression, Support vector machine, K-mean clustering, and neural networks.

As part of the MySQL DBMS course, I acquired knowledge of Database Architecture and Modeling, Entity-Relationship Model, Database Normalization, various SQL statements and techniques, Database Administration, and developed a project to fulfill the course requirements.

Through self-study, I learned R v4.2.2 Programming and used for statistical analysis and data visualization.

MatLab Programming provided a good understanding of various mathematical and numerical analysis tools and methods. Applied these techniques in practical applications and used this knowledge to complete the project required for my course work.

SKILLS

Technical Skills:

Programming Tools - Python 3.9 (with Library Packages NumPy, Pandas, Matplotlib,

SciPy), SQL, SAS 9.4, R 4.2.2, MatLab, Exsys Corvid Eval System

DBMS - MySQL 8.0

Devl & Analysis Tools - Jupyter Notebook IDE, Spyder IDE, Geany, MySQL Workbench,

vi editor, RStudio IDE, IBM SPSS

O.S. - Linux, Windows10

Doc. & Presentation Tools - MS Word, Excel, PowerPoint etc.

EXPERIENCE

Merck

Externship

Remote, 126 E. Lincoln Ave,

Rahway, NJ 07065

March 2021-March 2021

Externship through Reilly Program at the BOLD Center for

Advancing Women’s Professional Development

Edison Department of Health and Human Services

Staff Member

100 Municipal Boulevard, Edison, NJ

June 2013- 2015

Collected Edison census data through surveys and health violation reports.

Filed data entries on health code violations using Microsoft excel into township database, plotted map data points, worked collaboratively with health department members to set outreach goals based on compiled data.

254 Easton Ave, New Brunswick, NJ

August 2018- November 2018

Saint Peter’s Hospital - Lori’s Gift Shop

Staff Member

Worked at the cashier. Worked the POS system as well as opened and closed the store. Fixed computer issues and general technological issues such as the POS system. Greeted and assisted customers and hospital employees with gift shop services and sending gifts to patients.

Girls Career Institute at Douglass College

Elected Delegate

100 George St,

New Brunswick, NJ 08901

June 2016-August 2016

Hosted by Tewksbury Township Women’s Club

Language Proficiency – English, Telugu

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