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Meghna Muralidharan
XXXX@XXXX.XXX | (929)-(XXX) XXX-XXXX |Website: meghnamural.com | Linkedin: meghna-muralidharan | GitHub: meghnamural Education
MS Applied Mathematics, 3.94/4 GPA Fall 2018 – May 2020
New Jersey Institute of Technology, NJ
BSc. Mathematics, 9.33/10 GPA 2015 - 2018
Stella Maris College, Chennai, India
Activities and Societies: General Secretary, Math Club
Skills
Software : Python, R, SQL, MATLAB, Tableau, Google Cloud Platform, AWS, Hadoop, Microsoft Office suite
Technical : Machine Learning, Data Analytics, NLP, Data Mining, EDA, ETL Processing, Deep Learning, Data Visualization
Certifications: Stock Prediction and Math Functions using Python (Udemy), DAT204x: Introduction to R for Data Science (edX),
Optimization Techniques (NPTEL), Machine Learning with Python (edX)
Experience
Data Scientist Intern Jan 2020- Present
Gesture US Inc., NY, USA
 Project Lead - Time series analysis for sales forecasting during Valentine’s Day using Multivariate LSTM Neural Network
 Contributed to an 80% increase in sales during peak sales period based off data-driven decisions
 Worked on data requests from other teams - data source identification, data extraction using SQL and exploratory data analysis
using Python to provide data-driven recommendations to business problems
 Analysed 50,000 datapoints of user information using Python to discover trends and patterns in purchase and proposed marked
price revision to increase customer retention rates- built ETL pipeline to extract data into cloud function
 Built predictive models to analyse customer churn rates using statistical cost analysis and hypothesis testing
 Collaborated with marketing and operations teams and presented insights on Tableau to increase profitability
 Customer review analysis interactive dashboard using NLP:
 Performed sentiment analysis and LDA on reviews and analysed frequency distribution of positive and negative ngrams
 Built an interactive dashboard using TabPy to gain marketing insights and expanded target audience group by 20% -
found that flower crowns were trending this V-day
 Worked on the scalability of the dashboard to improve ease of use for the executive team Research Intern, RADLab (Data Science Lab NJIT)
Jan 2019- Dec 2019
New Jersey Institute of Technology, NJ, USA Objective: Modeled probability distributions using Python to study statistical marketing trends - customer response and retention rates
corresponding to a subscription-based business model
 Generated statistical marketing models - sBG,nBD,BBD distributions - to study trends of customer-based marketing strategies
 Imported 10,000 rows of consumer response data from a sampled population; analyzed customer retention rate using sBG and
determined the survival probabilities in Python and R
 Trained the dataset based on impacting factors like requirements of sampled group, familiarity with product design to name a
few and predicted trends for a future time frame
 Simulated a Choice Model to predict the effectiveness of monthly showings for outdoor billboard based on commuter response
 Studied various scenarios such as the location of the billboard, geographical factors, different times in the year and found the
exposure rate of the population to be a decreasing function of individual exposure rates Intern, Probabilistic Models and Statistics Jan 2017-July 2017
Indian Statistical Institute (ISI), Bangalore, India Objective: Studied population growth models using probability distributions
 Theoretical problem-solving covering statistical distributions-Beta, Gamma, Binomial, Geometric, Exponential Distributions, real-
life probability models and stochastic processes
 Assisted in the optimization of birth-death and population growth models of bacteria using Python
Personal Projects
Predict virality rate of the Coronavirus through DNN using Keras and estimate the likelihood of spread in New York City
 Created a pipeline to extract Coronavirus data and collected demographic and geographic data for different countries
 Developed a deep neural network and a Bayesian model to predict rate of spread of epidemic based on air passenger flow,
population density, proximity to healthcare facilities and predicted a 76% rate for NYC in the initial phase
 Achieved a 5.6% loss in model testing - hypothesized relation between virality of epidemic and virality of new brand in the market
Awards/Fellowships
Awarded EduCo Scholarship for Academic Excellence at NJIT 2018
University Rank 1 in BSc. Mathematics, Stella Maris College– Mathematics Gold Medalist 2018
Received a fellowship under the Summer Research Fellowship Program (SRFP), Indian Academy of Sciences 2017 Meghna Muralidharan
XXXX@XXXX.XXX | (929)-(XXX) XXX-XXXX |Website: meghnamural.com | Linkedin: meghna-muralidharan | GitHub: meghnamural Education
MS Applied Mathematics, 3.94/4 GPA Fall 2018 – May 2020
New Jersey Institute of Technology, NJ
BSc. Mathematics, 9.33/10 GPA 2015 - 2018
Stella Maris College, Chennai, India
Activities and Societies: General Secretary, Math Club
Skills
Software : Python, R, SQL, MATLAB, Tableau, Google Cloud Platform, AWS, Hadoop, Microsoft Office suite
Technical : Machine Learning, Data Analytics, NLP, Data Mining, EDA, ETL Processing, Deep Learning, Data Visualization
Certifications: Stock Prediction and Math Functions using Python (Udemy), DAT204x: Introduction to R for Data Science (edX),
Optimization Techniques (NPTEL), Machine Learning with Python (edX)
Experience
Data Scientist Intern Jan 2020- Present
Gesture US Inc., NY, USA
 Project Lead - Time series analysis for sales forecasting during Valentine’s Day using Multivariate LSTM Neural Network
 Contributed to an 80% increase in sales during peak sales period based off data-driven decisions
 Worked on data requests from other teams - data source identification, data extraction using SQL and exploratory data analysis
using Python to provide data-driven recommendations to business problems
 Analysed 50,000 datapoints of user information using Python to discover trends and patterns in purchase and proposed marked
price revision to increase customer retention rates- built ETL pipeline to extract data into cloud function
 Built predictive models to analyse customer churn rates using statistical cost analysis and hypothesis testing
 Collaborated with marketing and operations teams and presented insights on Tableau to increase profitability
 Customer review analysis interactive dashboard using NLP:
 Performed sentiment analysis and LDA on reviews and analysed frequency distribution of positive and negative ngrams
 Built an interactive dashboard using TabPy to gain marketing insights and expanded target audience group by 20% -
found that flower crowns were trending this V-day
 Worked on the scalability of the dashboard to improve ease of use for the executive team Research Intern, RADLab (Data Science Lab NJIT)
Jan 2019- Dec 2019
New Jersey Institute of Technology, NJ, USA Objective: Modeled probability distributions using Python to study statistical marketing trends - customer response and retention rates
corresponding to a subscription-based business model
 Generated statistical marketing models - sBG,nBD,BBD distributions - to study trends of customer-based marketing strategies
 Imported 10,000 rows of consumer response data from a sampled population; analyzed customer retention rate using sBG and
determined the survival probabilities in Python and R
 Trained the dataset based on impacting factors like requirements of sampled group, familiarity with product design to name a
few and predicted trends for a future time frame
 Simulated a Choice Model to predict the effectiveness of monthly showings for outdoor billboard based on commuter response
 Studied various scenarios such as the location of the billboard, geographical factors, different times in the year and found the
exposure rate of the population to be a decreasing function of individual exposure rates Intern, Probabilistic Models and Statistics Jan 2017-July 2017
Indian Statistical Institute (ISI), Bangalore, India Objective: Studied population growth models using probability distributions
 Theoretical problem-solving covering statistical distributions-Beta, Gamma, Binomial, Geometric, Exponential Distributions, real-
life probability models and stochastic processes
 Assisted in the optimization of birth-death and population growth models of bacteria using Python
Personal Projects
Predict virality rate of the Coronavirus through DNN using Keras and estimate the likelihood of spread in New York City
 Created a pipeline to extract Coronavirus data and collected demographic and geographic data for different countries
 Developed a deep neural network and a Bayesian model to predict rate of spread of epidemic based on air passenger flow,
population density, proximity to healthcare facilities and predicted a 76% rate for NYC in the initial phase
 Achieved a 5.6% loss in model testing - hypothesized relation between virality of epidemic and virality of new brand in the market
Awards/Fellowships
Awarded EduCo Scholarship for Academic Excellence at NJIT 2018
University Rank 1 in BSc. Mathematics, Stella Maris College– Mathematics Gold Medalist 2018
Received a fellowship under the Summer Research Fellowship Program (SRFP), Indian Academy of Sciences 2017