SUMMARY:

• Confidential has 10 years’ experience leading data science projects, maximizing his teams’ business insight and analytical creativity. Crysler has degrees
• Practical data science: Flexible skillset that incorporates data engineering, software development and statistical analysis. Applying machine learning algorithms within the Corporate Data Warehouse (CDW) and Cloud environments, including Deep Learning, Gradient Boosted Regression Trees, (Hierarchical) Time Series Forecasting, Regularization Path Models, etc.
• Deep consulting experience: Creation of complex deliverables including machine learning pipelines, production libraries, advanced visualizations, etc.
• Sound analytical approach: Relentlessly improves data quality and predictive accuracy.

TECHNICAL SKILLS:

Expert Skill: Python Data Science (pandas, numpy, sci - kit learn, scipy, xgboost, h2o, DARTS, OpenCV, PyTorch), R, Microsoft SQL Server (SSDT, T-SQL, SSRS)

Advanced Skill: Oracle PL/SQL, Teradata, MySQL

Intermediate Skill: Scala, Pig (Amazon EMR), Mathematica, MATLAB, Azure Cosmos DB

PROFESSIONAL EXPERIENCE:

Senior Lead Data Scientist

Confidential, Austin, TX

Responsibilities:

• Implementing the machine learning infrastructure for an international Internet of Things (IoT) Edge based platform.
• Leading the Machine Vision component of the platform, providing customer facilities with real-time throughput and defect monitoring.

Lead Data Scientist

Confidential, Austin, TX

Responsibilities:

• Implemented pipeline utilizing CUDA (GPU processing) to forecast long-range expected viewership (i.e. demand-side), expected market value of commercial inventory and expected sold units (i.e. supply-side). Components of the pipeline include:

Lead Data Scientist

Confidential, Austin, TX

Responsibilities:

• Implemented the budget forecasting platform utilized by the Confidential ’ ( Confidential ) to support the Mission Act ( https:// Confidential . Confidential .gov/ )
• The platform integrates 3 authorization and 5 claims processing systems across 6 servers and 11 independent schemas.
• The forecasting system uses two algorithms to model the sequence of Confidential spending on purchased, out Confidential t Confidential:

Statistician II

Confidential, Austin, TX

Responsibilities:

• Data architect and senior data scientist for a financial management tool used by over 100 offices within Confidential . Designed to improve compliance with GAAP standards, since 2017, the system has led to the re-allocation of ~$600m in previously reserved funds. The system is now fully implemented, assisting with the management of over $10b in annual expenditure for all Confidential purchased care programs.
• Created the back-end infrastructure (R & SSIS) that integrated data from 5 Confidential enterprise applications. Trained and deployed to production 3 machine learning models (xgboost and elasticnet) to estimate purchased care future liabilities.
• Created automated sampling package to evaluate business operations errors for Confidential ’s purchase care dialysis program (R & SSIS). The package parameterized confidence level, margin of error and estimated failure rate, allowing Confidential executives to customize the level of review for the department’s audit programs.

Analytics Manager

Confidential, Austin, TX

Responsibilities:

• Created a framework to select an optimal basket of test markets for a digital pilot program. The process evaluated 100+ markets’ revenue growth and competitive conditions to U.S. averages across 60 measures of similarity. The selection formula maximized the statistical independence of the markets while minimizing their collective variance to national measures. The selected markets were used for media planning strategy.
• Created an association rules procedure (a priori algorithm) to mine large-scale survey of customer perceptions. Within a dataset containing 400 questions for 12,000 respondents, procedure detected 5 response combinations that motivated customer purchasing decisions in ~80% of cases. Findings from the study supported annual strategic and creative media planning
• Created an Extract/Transform/Load (ETL) process to integrate data sources representing 20 distinct media channels (e.g. National Broadcast, Cable, Syndication, etc.). The final dataset was used to identity the optimal mix of media spending allocations for ~12 large U.S. local markets.

Senior Statistical Analyst

Confidential, Austin, TX

Responsibilities:

• Led data integration and credit model development for online lender using MySQL, R and SAS. Project included creating an Extract/Transform/Load (ETL) process to load 1 terabyte of files from 5 credit bureau sources. The final implementation partitioned the data into 5 sub-populations, applied a custom L1 regularization path algorithm for each group, and produced granular diagnostic output across the entire path.
• Developed User Activity DataMart. SSIS package automated activity logs ETL, generated a synthetic user key to track actions across source data and structured data for time series analysis.

Director, Data Science

Confidential, Hartford, CT

Responsibilities:

• Performed all database administration tasks for 3 terabyte pharmacy claims server supporting $2m in annual billings. Responsibilities included all Extract/Transform/Load (ETL), development (T-SQL), maintenance (SSIS), ad hoc reporting, and tuning.
• Implementation of Stochastic Boosting (ADA.M1 Algorithm) to optimize flag-based auditing procedure applying over 30 filters. Boosted tree-based ensemble reduced time to output by 25 hours; a 50% increase in performance.
• Design and implementation of case management data model and operational reporting solution, including ETL, into Oracle Datamart. Data model successfully integrated client’s operational activity data with case history information and was based on a source of 230 dimensional tables.

Applied Analytics Analyst

Confidential

Responsibilities:

• Led migration of mainframe SAS/DB2 Encounter Reporting System (ERS) to SAS/Oracle EDW solution. Responsibilities included development of views, testing, SQL Development Standards Guide and Extract/Transform/Load (ETL) documentation. Delivered SAS OLAP cube to automate data profiling review and analysis.
• Led migration of SAS Hospital Administrative Profile System to SAS/Teradata EDW solution. Completed this project without access to the original data source.