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Data Scientist Resume

TX

SPECIALIZES IN:

Machine Learning and Data Science

SUMMARY:

  • I am an overall industrial experience of 4 years and have worked in manufacturing, healthcare, marketing, retail and digital marketing analytics as well as business intelligence.
  • Data Management
  • Data Science
  • Machine Learning
  • Creating Dashboards
  • Data Analysis | Deep Learning
  • VBA | ETL | Advance Excel | MongoDB | Python | R/ SAS | Writing Algorithms | Statistical Analysis Python | R/ SAS | Writing Algorithms | Statistical Analysis

TECHNICAL PROFICIENCIES:

Areas of Excellence: Data Science, Data - Driven Analysis, Machine Learning, Deep Learning, Business Intelligence, Business Analytics, Tensorflow

Technical Skills: A/B testing, Data Mining, Decision Tree, Clustering, Statistical Analysis, Predictive Analytics, Data Visualization, Neural Network, PostgreSQL

BIG DATA: R, SAS, Python, Java, SQL, PL-SQL, Advance Excel, MS Access, Microsoft SSIS, SSAS, Tableau, SAP BI, SAP Net weaver, SCIKIT-LEARN, SAP HANA, LINUX, SIEBEL, ETL, Google Analytics, ORACLE 11g/10g/9i HADOOP, Apache Spark &Scala, MongoDB, Kafka, HIVE, Pig, HDFS

PROFESSIONAL EXPERIENCE:

Data Scientist

Confidential, TX

Responsibilities:

  • Performed study of Accountable Care Organizations to increase our understanding of their success through key indicators benchmarked by peer and national standards. Developed new methodology that focuses on relative performance in key performance indicators, normalized by group size, location, and medical risk
  • Created projection analysis of member populations that demonstrate member populations influence provider group success within fee for value plans
  • Developed and maintained Hadoop database system for reporting use that powers multiple reports in Tableau and MS Office Products and replaced previous methods of manual builds
  • Designed, created, and delivered a user friendly, scalable reporting suite for a wide audience, including Wall Street quarterly reporting, previous reporting only provided a single national view

Data Analyst

Confidential

Responsibilities:

  • Collaborated to implement A/B testing for an e - commerce website and created effective call-to-actions to improve CTR and Conversion Rate by 10%
  • Developed segmentation models using K-means Clustering in order to discover new segments of users
  • Conceptualized and implemented a sentiment analysis tool to rate the hotels based on subjective customer reviews
  • Conducted extensive research on revenue management and pricing analytics in the retail sector
  • Applied various machine learning techniques to build dynamic pricing models and maximize profits
  • Deployed multiple loss minimization and optimization technique with the help of statistical techniques and hypothesis testing and dealt with uncertainty in price fluctuations.
  • Created multivariate regression based attribution models using ad stock analysis from the digital marketing data
  • Conducted extensive research on revenue management and pricing analytics in the retail sector
  • Worked on data cleaning and reshaping , generated segmented subsets using Numpy and Pandas in Python.
  • Developed Python scripts to automate data sampling process . Ensured the data integrity by checking for completeness, duplication, accuracy, and consistency
  • Applied various machine learning techniques to build dynamic pricing models and maximize profits
  • Based on the historical data, predicted a customer’s likelihood to purchase products at a given point in time
  • Led the development pricing analysis platform including a scorecard dashboard created using k-NN Algorithm
  • Collected pricing data from different aggregators by performing web scraping in Python for competitive analysis
  • Applied various machine learning algorithms and statistical modeling like decision tree, logistic regression, Gradient Boosting Machine to build predictive model using scikit-learn package in Python.
  • Developed intricate algorithms based on deep-dive statistical analysis and predictive data modeling that were used to deepen relationships, strengthen longevity and personalize interactions with customers.
  • Developed advanced internal and external data sets to develop business insights and combine with insights.
  • Interpreted data, analyzed results using statistical techniques and provided ongoing reports for ad campaigns.

Software Engineer

Confidential

Responsibilities:

  • Identified fraud in the insurance claim with the help of unsupervised anomaly detection algorithm that helped reduce the false alarm by 20% and increased the efficiency of the claim management system
  • Assisted the team in collecting, cleaning and transforming data from different sources for big data analytics using SAP Net Weaver
  • Developed python script that regulated the approval of the payments and reserve of insurance claims under business constraints thereby increasing the customer database by 5%
  • Mined Customer data for Farmers Insurance and built a logistic regression model in R/Python to predict the probability of a customer buying auto insurance policy and achieved misclassification rate as 0.06
  • Used data mining and clustering technique , to assign claims to most appropriate adjuster based on experience and loss type thus improving the overall customer experience in terms of claim duration
  • Leveraged on BI tools like Tableau and Power BI to develop business dashboards enabling leaders for decision making and forecasting the number of claims monthly.
  • Generated a retention predictive model and improved c-stat value more than 85% in a Travelers competition to predict/forecast the most likely policies to cancel and understand key drivers to cause policy cancellation
  • Performed Data Exploration, Data Preparation, Data Cleaning and Data Visualization of the raw Customer data for Farmers Insurance and built classification model in R/Python/SAS to predict the probability of a customer buying auto insurance policy and improved the accuracy of the model by 13%
  • Used Data Mining and Clustering technique , to assign claims to most appropriate adjuster based on experience and loss type thus improving the overall customer experience in terms of claim duration
  • Used K-Means, Random Forest, Decision Tree, Regression, KNN, SVM, Neural Network, Naïve Bayes using SCIKIT Learn and Tuned the model with appropriate parameters using Lasso/Ridge Regression to determine claims that were likely to result in litigation

Confidential

Data Scientist

Responsibilities:

  • Launched an on - demand restaurant food delivery mobile app & website startup, acquiring 1700 customers in the first 6 months with 30% re-ordering rate
  • Gained high proficiency in gathering crucial requirements, creating use cases, user stories, prototypes, and MVP throughout the product lifecycle
  • Effectively implemented A/B testing to improve UI/UX and KPIs, increasing the revenue by 15%
  • Negotiated partnership contracts with major restaurants, contributing 60% to the revenue
  • Developed automation features to improve the order processing time by 37%, optimizing the food delivery time to just 35 mins from placing the order (within 2.5 miles radius)
  • Orchestrated low budget marketing campaigns, resulting in 27% growth from Q1 through Q3
  • Provided training, education and support to 8 interns on sales and marketing.

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