Sarvesh Rawat 980-***-**** firstname.lastname@example.org Dearborn, MI
LinkedIn: Sarvesh Port Folio : Click_Me
● Analytics professional with 3+ years of Industry and Research experience in Data Science and Big Data
Programming: SQL, R, Java, Matlab, SAS, Python (Pandas, Sci-kit, Numpy, Scipy).
Big Data: Apache Spark, Hive, Hadoop Ecosystem, MapReduce.
Tools: Tableau, D3.js, Excel, AWS, NoSQL, Azure ML, Power BI, Google Analytics, SSIS, SSAS, SSRS.
Data Science: Statistics, Algorithms, Data manipulation, Experimental Design, Hypothesis test, Predictive Models, AI, Data mining, Time Series, Business Intelligence, ETL, NLP, Probability.
Soft Skills: Statistical, Analytical, Quantitative, Intuitive, Fast-paced, Proficient, Attention to detail.
Ford Motors Company (Global Data Insight Analytics) Data Science Analyst Dec 17- Present
Integrate various data sources and process billions of records for Feature engineering and pre-profiling using Hive and Spark.
Built different customer preference models using advanced Machine Learning to support Ford market strategies for global market.
Built automated scripts for data blending and ML workflows for advanced analytics using Alteryx.
Berkshire Hathaway (Oriental Trading Company) Data Scientist Intern May 17- Sept 17
5.0% increment in the summer sales in identified key areas by improving the Conversion Rate.
Processed 100 million of records to identify the most crucial factors from 160+ factors using Regression and RF that drives Conversion and Retention rate.
3.0 % increase in ROI by improving the promotional strategy for the Coupon codes and discounts, according to the customers purchasing behavior.
Saved 500+ man-hours annually by building an automated classifier using Text mining (NLP) for user complaint & product review.
Toyota North America (Cognizant Technology Sol) Data Analyst Sept 15- July 16
10% Click-through Rate increment by designing a targeted E-mail promotional strategy using Ensemble models and Regularized logistic regression.
Developed interactive dashboards/reports for senior management such as customer retention (RFM analysis) using SQL and Tableau.
Predicted sales growth using Time Series analysis using ARIMA modelling to carry out various A/B testing.
Collaborated with IT team to create automated data foundations & provide strategic recommendations to senior management.
Ashok Leyland, India Data Analyst Intern May 14 - Jan 15
Gathered, cleaned, and analyzed millions of records for doing Root Cause Analysis of the faults in the plant.
Saved 500+ man-hours by developing a R- shiny based KPI dashboard to visualize real time production metrics and performance of each department for executive leadership.
Improved plant efficiency by identifying faults in the production line and departments using Predictive models and Text Mining.
University of North Carolina, NC Research/Teaching Assistant Aug 16 - Dec 17
Cleaned the unstructured data (NoSQL) from the logs provided by “WALLMART.COM”.
Analyzed customer behavior from 70+ factors including demographics, price, marketing channels, search etc. to identify trends.
Regrouping items into various categories using Market Basket Analysis and Clustering according to requirements.
Reduced Dimensionality with PCA, built models to predict customer purchase using XGBoost and Ensemble models.
Customers Segmentation for improving Retention rate based on Survival Analysis and Customer LTV.
VIT University, India Data Science Research Assistant May 13 - Aug 2015
Collaborated in several International projects in the field of Data Science and Machine learning to provide solutions in Electrical system, E- Commerce, Finance, Cyber security and Health care problems.
“National Innovators Challenge Award (2013-14) ” by Danfoss North America. Second runner up in INDIA.
Making Grids Smarter using Data Science: Built a hybrid classifier by analyzing data to predict faults in Electrical Transformers.
“Multi-sensor data fusion by a hybrid methodology–A comparative study”. Computers in Industry, 75, pp.27-34. (2016)
“A dominance based rough set classification system for fault diagnosis in electrical smart grid environments”. Artificial Intelligence Review, 46(3), pp.389-411. (2016)
* Please find rest of my research publications here: : Sarvesh_Publication
Recommendation System: Movie Recommendation System using KD Tree and Collaborative Filtering
Real time movie recommender system that asks for a sample movie from user and recommend similar kind of movies.
Visualization: A dashboard for “Daimler Trucks North America, North Carolina”
Developed Shiny based KPI dashboard to track vehicles down the line and visualize the plant performance.
Big Data Analysis: Classification system for Credit Risk Evaluation in Financial Banks using HIVE on Hadoop and Apache Spark.
Analyzed data provided by German bank to build a model to discriminate between a good and bad credit
Text Mining: Customer sentiment analysis on product reviews and user complains.
Performed sentiment analysis using Text Mining. Built a classification model using word cloud, N-gram and Topic Modelling.
University of North Carolina, Charlotte, NC 2016- 2017
MS in Computer Science (Data Science) GPA: (4.0/4.0)
VIT University Vellore, India; 2011- 2015
BS in Electrical Engineering GPA: ( 3.5/4.0)