Pavan Kumar Kanchanapalli

Ph.: 208-***-****

Email: ac8kho@r.postjobfree.com

Professional Summary:

Microsoft Certified Data Science professional with Ten plus years of experience in all phases of diverse technology projects specializing in Data Science, Azure Machine Learning and Tableau.

Worked on analyzing large datasets on distributed databases and developing Machine Learning algorithms to gain operational insights and present them to the leadership.

Extensively involved in Data preparation, exploratory analysis, Feature engineering using Supervised and unsupervised modeling.

Well versed with Linear/non-linear, regression and classification modeling predictive algorithms

Actively involved in Model selection, Statistical analysis using Gretl Statistical Tool

Created dashboards as part of Data Visualization using Tableau and Power BI

Performed preliminary data analysis using descriptive statistics and handled anomalies such as removing duplicates and imputing missing values using Talend tool

Performed Dimensionality reduction using near zero variance and correlation techniques.

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

Performed multiple Data Mining techniques and derive new insights from the data

Team player with good logical reasoning ability, coordination and interpersonal skills

Able to complete projects independently as well as within a team environment

Team builder with excellent communications, time & resource management & continuous client relationship development skills.

Technical Expertise:

R Programming

R Studio

Azure Machine Learning

Tableau & Power BI

Talend Data Preparation Tool

Github

PL/SQL

Microsoft Office

MS-Access

Python

Education

MS, Civil Engineering, Major in Structural Data Analytics (Statistical Analysis) Aug 2007 from Lamar University, TX.

BS, Civil Engineering, April 2003

Formosa Petrochemicals, May 2015 to Present

Data Scientist

Responsibilities:

Designed applications of Machine learning, Statistical Analysis and Data visualizations with challenging large data processing problems.

Involved writing the mapping specifications for converting the legacy building and warehouse datasets

Worked 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

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

Integrated SAS datasets into Excel using Dynamic Data Exchange, using SAS to analyze data, statistical tables, listings and graphs for reports.

Performed data analysis on the datasets using Proc Print, Proc Sort, Proc Transpose, Proc Means, Proc Summary, Proc Tabulate, Proc Univariate And Proc Freq .

Performed Data management like Merging, concatenating, interleaving of SAS datasets using MERGE, UNION and SET statements in DATA step and PROC SQL.

Experience in using SAS to read, write, import and export to another data file formats including delimited files, spreadsheet, Microsoft excel and access tables.

Worked closely with Business users in gathering the requirements for project documentation and generated report

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 of time 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.

Formosa Petrochemicals, Irving, TX October 2007 to April 2015

Senior Data Analyst

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.

Built an Interactive Search Engine Interface

Analyzed customer consuming behavior and discover value of customers.

Applied customer segmentation with clustering algorithms and develop geo-demographic customer segmentation models.

Developed personalized products recommendation with Machine Learning algorithms including Collaborative filtering and Boosting Tree, Deep Learning, Natural Language Processing to better meet the needs of existing customers and acquire new customers using Python and R studio.

Developed programs for Listings, Summary tables and Patient profile as per the study requirement.

Delivered Interactive visualizations/dashboards using ggplot2, MatplotLib and Tableau to present analysis outcomes in terms of patterns, anomalies and predictions.

CORE LOGIC, Hyderabad India August 2003 to November 2004

Business Data Analyst

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-ordinate with various business users, stakeholders and SME to get Functional expertise, design and business test scenarios review, UAT participation and validation of financial data.

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