PROFESSIONAL SUMMARY:

• Microsoft Certified Data Science professional and IIBA Certified Business Data Analyst with six plus years of experience in all phases of diverse technology projects specializing in Data Science, Azure Machine Learning and Tableau
• Proficient in the entire CRISP - DM life cycle and actively involved in all the phases of project life cycle including data acquisition, data cleaning, data engineering
• Experienced in writing complex SQL queries in performing Data analysis using window functions, joins, improving performance by creating partitioned tables
• Performed preliminary data analysis using descriptive statistics and handled anomalies such as removing duplicates and imputing missing values using Talend data preparation tool
• Extensively involved in Data preparation, Exploratory analysis, Feature engineering using Supervised and unsupervised modeling.
• Performed operations on analyzing large datasets on distributed databases and developing Machine Learning algorithms to gain insights
• Well versed with Linear/non-linear, regression and classification modeling predictive algorithms
• Highly skilled and knowledgeable in Model selection, Statistical analysis using SPSS/ R
• Experience in Implementing Machine Learning Algorithms
• Time series modeling/forecasting
• Artificial Neural networks
• ANOVA
• Random forests
• Markov Chain Monte Carlo Methods
• Hidden Markov Models
• CART, CHAID
• Multivariate analysis k-means Clustering
• Support vector machines
• A/B testing
• Data Visualization
• Experience working with various databases like Oracle, Teradata, DB2, Netezza and performed the computations, log transformations, feature engineering, and Data exploration to identify the insights and conclusions from complex data using R- programming in R-studio
• Validate the consolidated data and develop the model that best fits the data. Interpret data from multiple sources, consolidate it, and perform data cleansing using R Studio
• Expert in creating Dashboards and visualize data using Tableau, matplotlib, ggplot to provide visibility for detailed analysis. Familiar with various variance and correlation techniques
• Experienced in various Data Mining techniques and knowledgeable in derivation of new insights from the data
• A complete team player with good interpersonal skills, logical reasoning, and always looking to motivate people around me
• Able to complete projects in a team or independently depending on requirements
• Able to form good relationships with Clients, SMEs, customers, colleagues, etc. providing excellent communication, time management, and feedback

TECHNICAL EXPERTISE:

R Programming

AWS | EC2 | Redshift

PL/SQL | HIVE

Python Programming

Jupyter Notebook

Talend Data Preparation Tool

Azure Machine Learning |H2O

Tableau

Apache Spark | Hadoop | MapReduce

PROFESSIONAL EXPERIENCE:

Data Scientist

Confidential, Plano, TX

Responsibilities:

• Design applications of Statistical Analysis and Data visualizations with challenging large data processing problems dealing with Health care clinic data along with Investment risk analysis.
• Involve writing the mapping specifications for converting the legacy building and warehouse datasets
• Advance skills with various databases and performed the computations, log transformations, Data exploration to identify the insights and conclusions from customer medical history data using R- programming in R-studio
• Perform in-depth statistical analysis and data mining methods using R, including Cluster analysis, Logistic Regression, and boosting models
• Extensively used Azure Machine Learning to set up the experiments and creating Web services for the predictive analytics
• Perform feature scaling, feature engineering and statistical modeling.
• Work on writing complex SQL queries in performing Data analysis using window functions, joins, improving performance by creating partitioned tables,
• Prepare multiple dashboards using Tableau to visualize Health care data and worked with all aspects of regression models to determine the payments of medical procedures as well as investment risk classification
• Responsible for working with stakeholders, SMEs to troubleshoot issues, communicate desired goals, issues, and findings to ensure all team members are on the same page

Associate Statistical Analyst

Confidential, Auburn, AL

Responsibilities:

• Designed applications of Machine learning, Statistical Analysis and Data visualizations with challenging large data processing problems resulting in savings more than $1.2M an year.
• Worked working with various databases like Oracle, SQL and performed the computations, log transformations, feature engineering, and Data exploration to identify the insights and conclusions from complex data using R- programming in R-studio
• Implemented predictive models using machine learning algorithms linear regression and linear boosting algorithms and performed in- depth analysis on the structure of models, compared the performance of all the models and found tree boosting is the best for the prediction.
• Applied concepts of R-squared, R.M.S.E, P-value, in the evaluation stage to extract interesting findings through comparisons.
• Performed in-depth statistical analysis and data mining methods using R, including Cluster analysis, Logistic Regression, and boosting models that led to reducing variance by 45%
• Proficient in the entire CRISP-DM life cycle and actively involved in all the phases of project life cycle including data acquisition, data cleaning, data engineering,
• Extensively used Azure Machine Learning to set up the experiments and creating Web services for the predictive analytics
• Performed feature scaling, feature engineering and statistical modeling.
• Worked on writing complex SQL queries in performing Data analysis using window functions, joins, improving performance by creating partitioned tables,
• Prepared multiple dashboards using Tableau to reflect the data behavior over period Analyzed and worked with all aspects of regression models (OLS etc.)
• Responsible for working with stakeholders to troubleshoot issues, communicate to team members, leadership and stakeholders on findings to ensure models are well understood and optimized.

Senior Supply Chain Data Analyst

Confidential

Responsibilities:

• Designed, modeled, validated and tested statistical algorithms against various data sets including behavioral data and deployed predictive models using R-studio
• Performed Data Transformation method for Rescaling and Normalizing variables.
• Applied different Machine Learning algorithms/methods on data sets to predict credit risk, fraud detection, customer churn, and target marketing.
• Worked on data to increase cross-& up-sell revenues, enhance customer value or reduce non-credit losses.
• Contributed implementing models to identify, extract, summarize, and reduce or categorize the relevant qualitative financial input information like sentiment/feedback/news according to specific structures (templates) from a source text (digital news) to support decision making.
• Analyzed, transformed, and contextualized a variety of ingested data - social data, GIS data, POI& AOI data, and some consumer behavior data for building direct marketing predictive models.
• Analyzed customer consuming behavior and discover value of customers.
• Applied customer segmentation with Clustering algorithms and develop geo-demographic customer segmentation models.
• Delivered Interactive visualizations/dashboards using ggplot and Tableau to present analysis outcomes in terms of patterns, anomalies and predictions.

Business Data Analyst

Confidential

Responsibilities:

• Prepared comprehensive documented observations, analyses and interpretations of results including technical reports, summaries, protocols and quantitative analyses.
• Worked closely with marketing team to deliver actionable insights from huge volume of data, coming from different marketing campaigns and customer interaction matrices such as web portal usage, email campaign responses, public site interaction, and other customer specific parameters.
• Gathered analyzed & translated business requirements into relevant analytic approaches & shared for peer review.
• Contributed to Finance and Risk management, Operations management, and Marketing to maximize ROI using Data Analytics
• Design, model, validate and test statistical algorithms against various real-world data sets including behavioral data and deploy models in the backend
• Performed Data Transformation method for Normalizing variables.
• Applied Business Objects best practices during development with a strong focus on reusability and better performance.
• Co-ordinated with various business users, stakeholders and SME to get Functional expertise, design and business test scenarios review, UAT participation and validation of financial data.