SUMMARY:

• An accomplished Data analytics leader with 8 years of experience in providing cost effective, data - driven, and risk-adjusted optimal solutions leveraging my expertise in Data Science, Discrete Optimization (LP, MIP, DP), Business Intelligence, Risk Management, Statistical Learning, Enterprise Architecture, and Project Management to improve decision making. My experience spreads across artificial intelligence, machine learning, constrained optimization, Natural Language Processing (NLP), Business Intelligence, data warehousing, and deep learning.
• Excellent experience in delivering practical and actionable insights to improve decision making, product quality, minimize warranty claims, maximize compliance, minimize risks, and reduce maintenance costs for manufacturing plants using predictive maintenance.
• Excellent knowledge of Hadoop architecture and ecosystem components including HDFS, MapReduce, Hive, Hue, HBase, PIG, Spark Core, SparkSQL, Spark ML, GraphX, Spark Streaming, Python, R, Mahout and Greenplum's MADlib.
• Strong earned value management (EVM) exposure and project risk management as well as monitoring and controlling the triple constraints to align with project objectives.
• Exceptional experience in IT architecture governance, building technology and application roadmaps, technology standards management, capacity planning, server sizing, and application portfolio management.
• Machine Learning
• Market Basket Analysis
• CRISP-DM/PMML
• Text Mining (NLP)
• Dimensionality Reduction
• Discrete Event Simulation
• Discrete Optimization
• Bayesian Decision Theory
• Genetic Programming
• Probabilistic Programming
• Deep Learning/Tensorflow
• Scrum Master
• Project Cost, Scope, and Schedule
• Project Planning
• Project Risk Management
• PMBOK/OPM3
• Project Budgeting
• Risk Strategies
• Critical Path Management
• TOGAF 9, FEAF, DODAF2.02
• IT Maturity Models (CMMI)
• IT Transformation
• IS Security Architecture
• Capacity Planning
• Business Transformation Readiness Assessment
• A truly collaborative and focused individual that has successful experience in the development and of peers, superiors and subordinates through thought leadership, innovative practices and industry best practices that is well grounded in practical experience.
• Developed a Data Science Strategy, Roadmap, citizen data scientist position paper, and advanced analytics tools evaluation criteria.
• Developing and deploying core statistical and machine learning algorithms for predictive analytics leveraging CRISP-DM methodology for project delivery.
• Delivered Market Basket Analytics leveraging Association Rules (Support, Confidence, Lift, and Leverage) using Apriori Algorithm data mining and modeling for United Supermarket's sales leadership.
• Employed Random Forest model to predict paint defects per vehicle along with a genetic algorithm to simulate optimal values for key variables to minimize paint defects.
• Designed and developed Internet of Things (IoT) diagnostic analytics to enable plant predictive maintenance for robots, machines, and vehicles for Toyota North America.
• Developed Telematics analytics roadmap and architecture; enabling connected vehicles Diagnostics, Predictive, and Prescriptive analytics using Azure Cortana Intelligence, Stream analytics, Azure Machine Learning, and Power BI.
• Research work involved experiment design, dimensionality reduction, multivariate statistical analysis, and optimization (Recommendation Systems).
• Conducted weekly status meetings to aid EVM, monitoring and controlling cost and schedule variances to keep project’s CPI and SPI within tolerable ranges.

TECHNICAL SKILLS:

Analytical Tools: Alteryx, Tableau, Microsoft Power BI, Alpine, STATA, SPSS, AMOS, PLS-SEM, OBIEE, IBM DSWB, Cloudera DSWB

Big Data Technology: Hadoop Ecosystem, HDFS, MapReduce, NoSQL, Hive, Pig, HBase, MongoDB, AWS Dev, OpenRefine, Kafka

R: Performance Analytics, Predictive Modeling, Ensembles, Shiny, NLP -Texting Mining, sparklyr, dplyr

Python: NumPy, SciPy, scikit-learn, Pandas, Matplotlib, Tensorflow, PyTorch, keras, Theano

Apache Spark: Spark Core, SparkSQL, SparkML, GraphX, Spark Streaming, PySpark, SparkR

Classification Methods: Decision Trees, K-Nearest Neighbor, Naive Bayes Classifier, Support Vector Machines, Neural Networks

Regression Methods: Linear, Multiple, Logistic Regression, Gamma Regression, RandomForest

Unsupervised Machine Learning: K-Means Clustering, PCA, CA, MCA, Hierarchical Clustering, Apriori Algorithm (Association Rules)

Deep Learning: Tensorflow, H2O, PyTorch, Keras, Theano

TimeSeries Modeling: AR, ARMA, GARCH, Exponential Smoothing

Statistical Analysis: Hypothesis Testing, Experiment Design, ANOVA, ANCOVA, MADlib, Mahout, Azure ML, Pandas, Numpy, Scipy

Multivariate Tools: MANOVA, MLR, MANCOVA, Path Analysis, Factor Analysis, Discriminant Analysis, Factorial Analysis of Variance

Optimization Tools: IBM ILOG CPLEX Optimization Studio (Linear &Integer Programming), Excel-Solver, Lingo, Alteryx, Genetic Algorithm

Delivered Use Cases: Predictive Maintenance, Text Mining, Anomaly Detection, Market Basket Analysis, and Process Optimizations.

Languages: Python, R, Scala, PMML, PL/SQL, SQL, SQL*Loader, XML, Java, C++

Platform: HP-UNIX, Solaris-UNIX, Linux Redhat 4/5/6, Windows Server NT/2003/2008, and Novell 4.x

Databases: Oracle 12c/11g/10g, Oracle TimesTen, DB2, Confidential 12/13/14, MySQL, MS SQL Server, Azure SQL Database, DynamoDB

Project Management Tools/Methodologies: Plainview, SharePoint, MS Project, Oracle AIM3.0/1, OUM5.5, PMBOK, CRISP-DM, Scrum, Agile

PROFESSIONAL EXPERIENCE:

Data Scientist

Confidential, Plano, TX

Responsibilities:

• Developed a Data Science strategy, Roadmap, Self-Service data science and advanced analytics evaluation criteria
• Presented data science tools evaluation and recommendations to Architecture Review Board
• Developed Telematics analytics roadmap and architecture, enabling connected vehicles Diagnostics, Descriptive, Predictive, and Prescriptive analytics using Azure Machine Learning, Real-Time analytics, and optimization tools.
• Developed vehicle diagnostic, predictive, and prescriptive analytics by conducting multivariate data preparation, factorial and multivariate analysis of variance, linear and multiple regression, path analysis, exploratory factor analysis, confirmatory factor analysis, and structural equation modeling.
• Lexus paint shop defects research involving dimensionality reduction with PCA, correlation (using performanceAnalytics package) and regression with Random Forest, and optimization (minimization) of defects per vehicle employing Genetic Algorithm.
• Leveraged Multinomial Naïve Bayes for NLP to qualitatively and quantitatively analyze NHTSA complaints, using methods such as document clustering, topic analysis, document classification, and sentiment analysis.
• Call Center Verbatim Analysis research to find the root cause call volume increase and predictive future staffing needs using NLP and texting mining to find the most frequently said words in calls.
• Vehicle warranty research involving feature engineering from a diverse range of data sources and predictive analysis to uncover the root cause of different kinds of warranties along with delivering warranty minimization application that implemented constrained optimization techniques.
• Led Toyota’s Manufacturing IoT analytics by formulating the strategy and roadmap for IoT analytics deployment; implemented edge analytics, diagnostic, predictive, and prescriptive analytics.

Predictive Analytics Architect

Confidential, Alexandria, VA

Responsibilities:

• Developed and presented a BI roadmap that is closely linked to the overall organizational strategic objectives. Project planning, scheduling, risk analysis, and monitoring and controlling project activities; working towards of identified project objectives.
• Delivered Financial Actuarial Analytics using SAS Enterprise Miner and R for a client managing 401K investment funds in Hartford, CT, along with CRM analytics.
• Server Sizing and capacity planning based on current state and target state applications and usage requirements.
• Installed and configured Hadoop components inclusive of MapReduce, HDFS, Hbase, Pig, Flume, Hive and Sqoop.
• Configure Sqoop for importing data into Hadoop's HDFS and exporting to Relational Databases. Installed and configured Weblech for web crawling integrating with Social media.
• Coordinating and integrating team building on individual efforts to forge a positive professional relationship with the client. Conducted a risk identification exercise and worked with management to mitigate identified risks.
• Developed the architecture, roadmap, and the Metadata to migrate and implement vendor metrics, vendor scorecards, Order guides, and Risk analysis reports; to capture vendor performance over a specified period and risks associated with engaging different vendors. On this Vendor scorecard project, I saved the client over $700,000.00 in 6 months in the development and support fees for the third party vendor who was engaged in developing the application that provided vendor management for United Supermarket chain (Albertsons Supermarket).
• Delivered Market Basket Analytics leveraging Association Rules (Support, Confidence, Lift, and Leverage) using Apriori Algorithm data mining and modeling for United Supermarket's sales leadership.

Data Scientist

Kemper Insurance Dallas, TX

Responsibilities:

• Worked with various databases like Oracle, SQL and performed computations, log transformations, feature engineering, and Data exploration to identify the insights and conclusions from complex data using R- programming in R-Studio.
• Designed, modelled, validated and tested statistical algorithms against various data sets including behavioral data and deployed predictive models using R-Studio.
• Applied concept of R-squared, R.M.S.E, P-value, in the evaluating stage to extract interesting findings through comparisons.
• Applied different Machine Learning algorithms/methods on data sets to predict risk, fraud detection, customer churn, target marketing and to set up the experiments and creating Web services for the predictive analytics.
• 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.
• Developed personalized products recommendation with Machine Learning algorithms including Collaborative filtering and Boosting Tree, to better meet the needs of existing customers and acquire new customers using Python and R Studio.
• Delivered Interactive visualizations/dashboards using ggplot2, Matplotlib and Tableau to present analysis outcomes in terms of patterns, anomalies and predictions.
• Prepared multiple dashboards using Tableau to reflect the data behavior over periods of time and worked with stakeholders to troubleshoot issues, communicate to team members, leadership and stakeholders to ensure models are well understood and optimized.

Oracle Developer

Confidential, Irving, TX

Responsibilities:

• Defined new Ledgers, defining value sets, Accounting Flexfield Structure, segments, Flexfield qualifiers, Security rules, cross-validation, accounting Calendar, and responsibilities.
• Configured Oracle Payables - Financial options, Payables options, Internal and external banks, payment programs, created Distribution Sets, and Payment Terms; along with an AIM BR100 document. Developed GL daily conversion rates SQL*LOADER program and a PL/SQL package to validate daily forex conversion rates and upload rates into the GL Daily Rates Interface; along with MD50/MD70.
• Configured Oracle Assets- Defined assets corporate books, tax books. Defined Prorate Calendar and conventions, setting up Asset Book Controls, Asset Categories, Fiscal Years, Calendars, System Controls, and depreciation methods.
• Converted standard AR customer invoice report and print statement reports into xml templates in BI publisher and developed xml bursting control files for these reports to be emailed directly to customers.
• Server Sizing and capacity planning based on current state and target state business analytics applications and systems usage requirements for a global consolidated business intelligence platform.
• Performed functional testing for existing modules to understand existing business process, created documents to understand functional requirements for interfaces. Leading assigned projects providing project planning and administration, issue resolution, monitoring project progress to plan, and obtaining and distributing project status.
• Worked with management on all Oracle EBS project related issues, changes, reporting and impacts ensuring that comprehensive information is provided to all stakeholders in a timely manner.