Data Scientist

Sree Lakshmi Sravya Duddupudi

959-***-**** *.******.***@*****.*** Cambridge MA 02141

LinkedIn GitHub

EDUCATION

Hult International Business School Cambridge, MA, USA

M.S. in Business Analytics August 2022

BML Munjal University. Haryana, India

Bachelor of Business Administration August 2019

DATA SCIENCE COMPETENCIES

Methodologies: SDLC, Agile, Waterfall, Statistics, CRM, CLV Language: Python, R, SQL, SAS, Scala, Java, C++ IDEs: Visual Studio Code, PyCharm ML Algorithm: Linear Regression, Logistic Regression, Decision Trees, Supervised Learning, Unsupervised Learning, Classification, SVM, Random Forests, Naive Bayes, KNN, K Means, CNN, Natural Language Processing(NLP) Packages: NumPy, Pandas, Matplotlib, SciPy, Scikit-learn, Seaborn, TensorFlow, Ggplot2 Big Data and Cloud Technologies: Apache hive, PySpark, AWS S3, AWS EC2 Skills: CLV, Google analytics, Marketing, MBTN Visualization Tools: Tableau, Power BI, QlikView, Google Analytics Database: SQL Server, MySQL, Hadoop, Spark Other Tools: Git, MS Excel Operating System: Windows, Linux

WORK EXPERIENCE

Hartford Financial Service Group Jan 2022 – Present

Data Scientist, Intern

Use Agile methodologies and scrum processes for project development.

Designing and implementing a data pipeline to extract 4TB of data into HDFS Cluster.

Designing and developing data wrangling and visualization techniques as well as a classification engine based on Logistic Regression.

Found issue with the current matching algorithm, implementing new matching algorithm to improve the data quality and hence data quality improved by 16%.

Led the analysis in SAS for data integration of mortality data using meta-analysis integration methods.

Dealt with Customer and prospect data and found 8% mismatch among the data using Apache Hive and PySpark.

Designing and publishing visually rich and intuitively interactive Tableau workbooks and dashboards for executive decision making.

Sundaram Finance, India Jan 2019-Aug 2021

Data Scientist

Designed Specification and Testing as per Cycle in both Waterfall and Software development Life Cycle methodologies.

Translated scientific and statistical designs to a developer based on common Python coding language.

Provided technical support on SAS programming related to data manipulation and analysis.

Designed and delivered five-day training on introduction to data science and research methods for public sector employees.

Developed machine learning models utilizing Logistic Regression and Random Forests to identify human characteristics and behavior to derive striking insights.

Developed technical documents and reports and design data visualizations to communicate complex analysis results.

Implemented supervised machine learning algorithms to predict the engine performance based on the selected features using multivariate regressions.

Implemented neural network to detect tampering activity using Kera’s and TensorFlow.

Performed the code version control on Git private repository.

RINL Steel Plant, India April 2018 - June 2018

Assistant - Corporate Strategy Department

Predictive Modelling Conducted a study on the previous sales of products and ran a predictive model that can help in estimating the possible number of sales when the products are sold in multiple bundles.

Carried out further research about the steel products when sold together save overall cost to the organization.

Business impact: This project paper was awarded the project of the year by the organization. This helped the organization to bundle their products not only based on their sizes but also the density and areas of sale.

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