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Data Analyst Sales

Wilmington, DE
December 23, 2019

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Naga Sai Suhas Somu 332-***-****


Data Analytics professional with 3 years of experience, developed and implemented business-focused data-driven analytical solutions. Expert knowledge of mathematical concepts and Statistical models. High proficiency in Python, R, SQL and TABLEAU EDUCATION

University of Connecticut School of Business Dec 2019 Master’s in Business Analytics & Project Management, 3.9 Coursework: Statistics in R, Predictive Analysis, Visual Analytics, Data Mining and Business Intelligence, Data Science with Python Vellore Institute of Technology University (VIT) May 2016 Bachelor of Technology, Mechanical Engineering, 3.45 Coursework: Linear Algebra, Calculus, C, C++, Database Management Systems, Object Oriented Programming, Operations Research SKILLS AND CERTIFICATIONS

Programming Languages & Tools: Python (NumPy, Pandas, Matplotlib, scikit-learn, TensorFlow), R, SQL, Snowflake, TABLEAU, Power BI, MS Excel, Oracle, Dataiku, Heap, JMP, SAS Enterprise Miner, MS Excel, Power Point, GGPLOT2, Anaconda-Jupiter Notebook Data/Business Analysis Techniques: Statistical Analysis, Machine Learning, Data Visualization, Regression (Linear & Logistic), Clustering (K-Means & Hierarchical), Decision Forests, Boosting, Random Forests, Outlier Analysis, Multivariate Analysis, XGBoost K-fold cross validation, Dimensionality Reduction (PCA), Neural Nets, Bootstrapping, Confidence Intervals, K-NN, Hypothesis Testing, Decision Modelling, Time Series Forecasting, Segmentation, Monte Carlo simulation, ETL, Descriptive & Inferential Statistics Certifications: Machine Learning (Stanford University, 2018), Customer Analytics (UPenn, 2018), Advanced Google Analytics PROFESSIONAL EXPERIENCE

Marlette Funding, LLC, Wilmington, DE

Data Scientist Intern, Python Power BI SQL Dataiku Heap Snowflake May 2019 - Present

• Developed and deployed logistic model with 76% accuracy on 12 Million records, for predicting close to 1.5 M potential customers to be included in marketing campaigns which lead to a projected 12% increase in origination fee

• Increased the number of leads received by 55% and reduced the customer acquisition cost by 38% by shifting the affiliate strategy from cost-per-loan to cost-per-lead and iteratively optimizing the strategy on a monthly basis to improve further

• Leveraged advanced analytics packages in python like Scikit-learn, Seaborn, NumPy, pandas and Matplotlib for data modelling

• Extracted data using complex SQL queries & created automated monthly projections report with KPIs like conversion rate, cost per lead etc. which is used by business owners and other analysts to understand the trends of KPIs and make business decisions

• Worked with channel managers, product, credit, data and BI teams to develop and maintain consistent metrics, reporting and monitoring around campaign/channel funnel conversion, return on investment and profit performance as well as campaign/ channel planning and forecasting

University of Connecticut, Hartford, CT

Graduate Teaching Assistant – Statistics in Business Analytics R Dec 2018 - Present

• Involved in the development of new course material, created assignments and prepared in-class activities which enable in-depth understanding and practical viewpoint of the course to students Capital Community College (CCC), Hartford CT Jan 2019 – May 2019 Analytics Consultant Python SAS JMP TABLEAU

• Identified the factors responsible for the student drop out, and provide insights which can increase the overall retention by 9%

• Implemented K-Means clustering and developed a logistic regression to predict the probability of retention at student level Cognizant Technology Solutions, Hyderabad, India Jul 2016 – Jun 2018 Data Analyst Python TABLEAU Excel SQL

• Driver Analysis: Led team of 3 analysts working on driver analysis model to identify major drivers responsible for decline in sales of a blockbuster drug accumulating ~80% of client portfolio through Linear Regression; and provided strategic recommendations

• Customer Segmentation: Created customer segmentation list using hierarchical clustering technique based on historical sales activity and behavioral metrics to help customer targeting for a launch product in specialty market ACADEMIC PROJECTS

Sign Language Prediction Python Nov 2018 – Mar 2019

• Built a visual recognition algorithm to recognize American Sign Language which can help the deaf and hard hearing

• Created a CNN model with 92% accuracy which classifies and maps the American Sign Language images to English alphabets

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