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Data Scientist Resume

Dallas, TX

PROFESSIONAL SUMMARY:

  • Data Scientist with 5+ years of experience in machine learning, Quantitative Research and Analytics, Anomaly detection and risk modelling, predictive modelling, Credit Risk Modelling, exploratory data analysis and data engineering across Banking & Financial Services and Semiconductor Manufacturing
  • Drove strategic business decisions using Quantitative Research methods used include ANOVA, MANOVA ANCOVA, Computational Modelling, propensity score matching, regression analysis and linear programming
  • Delivered significant cost savings through Machine learning models using decision trees, neural networks - perceptron/MLP, Recurrent Neural Networks (RNN), LSTM and Convolutional Neural Networks (CNN)
  • Developed forecasting models using time series analysis, and non-parametric regression techniques - loess regression, splines etc. to streamline operations management and capacity forecasting
  • Designed, Developed and Delivered intuitive visualization using Tableau 9/10/2019 and ggplot
  • Tableau Certified professional with rich experience in projects involving end to end BI DSS/GDSS implementations that illustrate intuitive analysis based on data research, operations reviews and other related parameters
  • 5+ years of proficiency in R & Python using R/R Studio/ Spyder/Pycharm for implementing various machine learning algorithms to develop ensemble model for addressing business problems
  • 16 years of overall IT experience across Data Analytics, Business Intelligence, Software Development and Maintenance projects
  • Experienced in driving, evolving, managing and continuously improving business intelligence programs of varying scales
  • Successful customer implementations using enterprise data integration solutions by developing and capturing repeatable best practices
  • Academic knowledge of RPA using UI Path
  • Scrum Master Certified (SMC) & ITIL V3 Foundation certified
  • Currently researching on Music Information Retrieval (MIR) from polyphonic sounds

DATA SCIENCE SKILLS:

R, Python, SAS, Tableau 9/10, Data Robot, UI Path RPA, MATLAB, Octave, Keras, TensorFlow, OpenCV, Oracle, AWS, Hadoop, RDMBS, No SQL, PL/SQL, Data Analytics, Anomaly Detection, Mortgage Origination & Servicing, System Analysis, Analytics implementation - DSS, GDSS, Model development, Database design & implementation (RDBMS & Non-RDBMS), project/program management, delivery management, Agile and SDLC

WORK EXPERIENCE:

Confidential, Dallas, TX

Data Scientist

Responsibilities:

  • Perform quantitative research and analysis to identify differences in characteristics of various claim specific attributes
  • Conduct exploratory analysis (EDA) - probabilistic modelling (frequentist & Bayesian), distribution fitting and parameter estimation, random sampling, data analysis, data modeling and model evaluation
  • Develop supervised & unsupervised machine learning algorithms to evaluate underlying anomaly data patterns and subsequently develop predictive models primarily focusing on risk evaluation and loss recovery
  • Data gathering (multiple sources), transformation / engineering and Develop intuitive dashboard to illustrate outcome of EDA using Tableau
  • Present analysis findings to executives for informed decision making - Weekly update to project managers and Biweekly presentations to Directors and team
  • Cluster analysis - identify most dense cluster and derive characteristics of the cluster -

Techniques used: Credit Risk Modelling & Anomaly Detection, Linear & non-linear regression, Poisson regression, Classification - logistic regression, kNN, Support Vector Machines (SVM), Random Forest, Logistic Regression, Linear Regression, loess regression, polynomial regression, ID3, C5.0, CART, Feed Froward Neural Networks (FFNN), Recurrent Neural Networks (RNN), Cluster Analysis - kMeans, K-medoids, Fuzzy Clustering, EM and DBScan, Time Series Analysis, statistical significance test - Repeated Measures ANOVA with unbalanced design, statistical significance tests

Tools: R/ R studio, Python, Data Robot, SAS, Tableau 10.5, Oracle, SQL, PL/SQL, Toad, AWS, PostgreSQL

Confidential, Dallas, TX

Data Scientist

Responsibilities:

  • Data gathering, transformation and engineering
  • Analyze inflow vs outflow volume and develop forecasting models for each channels/source of expense lines
  • Based on analysis findings, recommend optimal thresholds for monitoring load volume
  • Provide weekly update to project managers
  • Presentations to Directors and QC managers on analysis findings

Techniques used: Time Series Analysis - SMA, Holt Winters, Non-linear Regression, statistical significance tests - proportion test and Cochran Q-test

Tools: used: R, R studio, Tableau 10.5, Oracle

Confidential, Dallas, TX

Data Scientist

Responsibilities:

  • Understanding processing differences using processing guide and servicing guide as this category has state level thresholds
  • Data gathering, transformation and engineering
  • Perform analysis of variance and post hoc tests to determine the states with most significant difference
  • Analyze characteristics and generate sample of anomalies by performing anomaly detection using various techniques
  • Pull all anomalies lines from source system and generate flat files containing those lines for loading into QC system
  • Develop research paper containing analysis findings for internal publishing

Techniques used: Descriptive Analytics, factor analysis., Classification - Logistic Regression, Random Forest, Rpart and NNet, Anomaly detection - Z score, distance based (Mahalanobis) and clustering.

Tools: used: R, R studio, Tableau 10.5, Oracle

Confidential, Dallas, TX

Data Scientist

Responsibilities:

  • Data gathering, transformation and engineering
  • Perform analysis of variance and post hoc tests to determine the subcategory with most significant difference since there are multiple subcategories under property inspections
  • Perform descriptive analytics and factor analysis to analyze characteristics and generate sample of anomalies by performing anomaly detection using various techniques
  • Pull all anomalies lines from source system and generate flat files containing those lines for loading into QC system
  • Develop research paper containing analysis findings for internal publishing
  • Automate anomaly detection so that it can be scheduled as repeated process

Techniques used: Descriptive Analytics, factor analysis., Classification –Logistic Regression, Random Forest, Rpart and NNet, Anomaly detection – Z score, distance based (Mahalanobis) and clustering.

Tools: used: R, R studio, Tableau 10.5, Oracle

Confidential, Dallas, TX

Data Analyst

Responsibilities:

  • Perform Data engineering, data scrubbing and data profiling on various types of tasks
  • Perform descriptive analytics to extract characterstics and behavior of each analyst
  • Developing score cards and KPI based on analysis
  • Develop a tool to recommend task allocation

Techniques used: Descriptive Analytics, factor analysis., AHP, ANOVATools used: R, R studio, R Shiny, Tableau 10.5, Sharepoint, VBA

Confidential, Austin, TX

Lead Analyst

Responsibilities:

  • Develop Test repoting & analytics framework
  • Drive test management function across multiple projects - strategy, planning & design, Effort estimation, Test execution, defect management etc.
  • Perform system analysis based on LiveCompare data to analyze impact on SAP objects and draw inferences
  • Identify, strategize and Implement process improvement & optimization across testing function by leverage data analytics & data science techniques
  • Operate as “Metrics Champion” of the team – develop metrics framework for testing COE
  • Collaborate with service providers for non-SAP apps testing – performance testing, automation testing and manual testing
  • Perform data analysis on test execution and defect data across projects to identify gaps and potential areas of improvement – exploratory data analysis, factor analysis, sentiment analysis and text mining
  • Develop predictive models in test execution and defect management – classification & regression, time series analysis
  • Manage performance testing needs for non-SAP apps area

Tools: Tableau 10.1, R/R-Studio, MS SQL Server, HP ALM 12.1, Livecompare, Sharepoint 2013, MS Visio, MS Office suite, linear regression and logistic regression

Confidential, Austin, TX

Business Data Analyst

Responsibilities:

  • Development of intutitive DSS system illustrating KPI’s relevant for various levels of executives & managers leverage data science concepts to develop timeseries forecast models use probablity modelling techniques to support exploratory data analysis implement machine learning techniques – clustering, classification and association rules to undermine hidden data patterns and inferences
  • Utilize AHP, exploratory analysis, PCA, predictive modelling & process optimization
  • Perform system analysis from a “data” perspective on existing systems and identify potential opportunities to enhance data scalability and availability
  • Develop optimization tools – has developed data validation tool and resouce allocation tool using AHP techniques which implements weighted model to allocate resources to tasks
  • Operate as “Analytics Champion” of the team – performing statistical analysis for the team there by resolving problems by combining tools & business knowledge
  • Participate in daily scrum meeting & generate weekly status report
  • Collaborate with other data analysts and address data issues / concerns
  • Support business teams in periodic & adhoc reporting

Tools: & concepts used:R, Python, Tableau 9.3.5/9.1, Oracle 12g, LoanSphere, Sharepoint 2013, MS Visio, Altova MapForce, MS Office suite, ERWin, Linear Regression, classification using Logistic Regression and kNN, kmeans clustering and Time Series Analysis

Confidential, Richardson, TX

Business Data Analyst

Responsibilities:

  • Conduct data mapping, exploratory data analysis, logical data modelling and gap analysis - between soruce & destination systems
  • Understand current business process, gather data associated with each process and perform descriptive / exploratory analysis to understand data gaps in comparison with new system
  • Perform business analysis & data analysis – exploratory analysis, risk analysis
  • Conduct data migration – from source to target – dealt with 50+ tables
  • Identify areas of potential data conflicts and resolve them
  • Architect destination data structure and prepare data for migration based on analysis
  • Identify data sets for model development based on business problems
  • Gather requirements for database changes & present it in CAB for review and approval
  • Participate in daily scrum meeting & generate weekly status report
  • Collaborate with other data analysts and address data issues / concerns

Tools: & concepts used: Oracle 11g, PL/SQL, Tableau 9.0, HP ALM 11.2, Clearcase 8, Sharepoint, MS Visio, MS Office suite, SonarQube, Cassandra.

Confidential, Austin, TX

Analyst

Responsibilities:

  • Perform system analysis based on LiveCompare data to analyze impact on SAP objects and draw inferences
  • Identify, strategize and Implement process improvement & optimization across testing function by leverage data analytics & data science techniques
  • Operate as “Metrics Champion” of the team – develop metrics framework for testing COE
  • Collaborate with service providers for non-SAP apps testing – performance testing, automation testing and manual testing
  • Perform data analysis on test execution and defect data across projects to identify gaps and potential areas of improvement – exploratory data analysis, factor analysis, sentiment analysis and text mining
  • Develop predictive models in test execution and defect management – classification & regression, time series analysis

Tools: & concepts used: Tableau 10.1, R/R-Studio, MS SQL Server, HP ALM 12.1, Livecompare, Sharepoint 2013, MS Visio, MS Office suite, linear regression and logistic regression

Confidential, Austin, TX

Delivery Manager

Responsibilities:

  • Governance of overall support function across technologies including sharepoint, MSBI, lotus notes & MSPe along with end to end management of managing multiple small-size IT projects Project
  • Review solution architecure, design & implementation of changes
  • Support incident analysis – Descriptive & Predictive
  • Identify risks & areas of continous improvement based on data analysis
  • Develop transition plans & schedules for transition engagements.
  • Ensures that projects are completed on time, on scope, on budget and with quality.
  • Communicates project status, progress on deliverables, and risks/issues to stakeholders and leadership in a timely manner.
  • Collaborates with cross-functional teams including architects, software engineers, developers, testers, technical leads, and deployment leads to ensure timely delivery of projects.
  • Process compliance monitoring & Risk management
  • Overseeing Change Management, Problem Management & Incident Management - SLA Monitoring & compliance management
  • Maintain project tracking and resolve project issues
  • Defining, monitoring & tracking continous improvement opportunities in line with high level organizational objectives
  • Transistion Management: Monitored, managed, tracked transition of various applications & integrated them into the main stream engagement following an acquisition of another semiconductor manufacturing compnay by the client

Tools: used: Sharepoint 2010/2013, Visio, MSPE, HP ALM 11.2, HP PPM 9.2, MS Office suite, MS Visio, Oracle, MS SQL Server, SSIS,SSRS, MS BI,SaaS – Workday & Kronos,Agile/ SCRUM

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