OBJECTIVE:

• Seeking an opportunity to continue as a frontline, hands - on, and in-depth technology and analytics leader dat leverages career achievements and a strong technical skill-set to influence and guide corporate strategy and industry focus. Relied upon to significantly enhance operational performance, clarify business objectives, ideation/creation of data-driven cognitive products, and create corporate presence in teh marketplace.

TECHNICAL SKILLS

Data Visualization and Analysis Tools: Full SAS v9.3 library (Enterprise Guide v4.3, Enterprise Miner), Microsoft SQL server 2005/2008R2/2012 BI Stack (SSIS, SSMS, SSRS), Oracle 11gi, Tableau (Desktop and Server), Microstrategy V9.0, Excel (Macros, Pivots etc.), SPSS, R (Rstudio/RMR), D3.js

Programming Languages: Java, T-SQL/PL-SQL, PHP, Perl, Python (2/3, Jython/Iron), Ruby/Rails, HiveQL, SAS, PIG Latin, C++, Scala

Data Management Platforms and Utilities: SQL Server 2005/ 2008R2, Oracle 11gi, IBM DB2, Teradata, MongoDB, Hadoop, HBase, MySQL, Cassandra, CouchDB, Hive, GreenPlum (v3.3.7, v4.2), StormDB, CouchDB, Riak, Microsoft MAPS/PDW, Oracle Exadata, Spark, Microsoft Azure, AWS

Data Management Tools and Techniques: Kimball and Inmon Methodologies, Embarcadaro, ERwin, Informatica Data Explorer and PowerCenter, SAS DataFlux, ClearCase, Perforce, Vault, SSIS (2005/2008), Talend, Profisee, Informatica MDM

Advanced Analytics Techniques and Methodologies: Predictive/Prescriptive modeling, deepnets, clustering, conjoint analysis, time series, NLP, classification trees, HMM, Collaborative filtering, Graph analysis

Data Warehousing and Architecture Skills: Construction of OLAP, ROLAP, and MOLAP cubes.

PROFESSIONAL EXPERIENCE

Confidential

Head of Data Science

Responsibilities:

• Led teh ideation, development, and launch of teh first data-driven cognitive salary and compensation marketplace platform using python, spark, predictive modeling, and phonetic entinty resolution, and acrony expansion.
• Created a patent pending entity resolution engine designed to create a 360 view of teh customer using RFM scoring and a proprietary phonetic matching algorithim.
• Led technical due dilligenece on 25 separate efforts for M&A activity to assess value and potential usage of data in cognitive data products.
• Responsible for teh oversight of 20 member offshore development team in Xian and Chengdu, China.
• Partnered wif a fortune 200 insurance company on teh creation of a computer vision algorithim designed to automatically extract features from images.
• Analytics liaison between Confidential Equity Partners and potential business partners including a fortune 200 insurance provider, a $40bn AUM hedge fund, and various other private equity firms.
• Provided guidance on implementing, hiring, and managing data science teams for 30 portfolio companies.
• Created forecasting algorithim dat predicted portfolio company performance.
• Provide technical guidance and thought leadership on data science to Confidential portofolio of companies.

Confidential

TEMPPrincipal - Advanced Analytics and Data Science

Responsibilities:

• Working wif teh architecture and innovations team, primary responsibilities included spear-heading technical development of global information management and analytics platform.
• Responsible for technical design and architecture of globally distributed, multi-tenant environment dat supported advanced analytics and reporting.
• Lead development of intelligent data pipelines, processing, and storage framework; along wif teh implementation of decisioning algorithms supporting critical business initiatives including asset reconciliation, fraud detection, portfolio balancing, and trade strategy (fund dependent).
• Lead practical application of data science for globally distributed analytics team. Techniques used included both linear/non-linear models as well as advanced analytical techniques including survival analysis and machine learning.
• Lead re-development of raw materials trade intelligence data analytics environment and warehouse
• Re-architected, Developed, Tested, and Deployed Kimball based data model aimed at providing greater
• insight into raw goods trade performance..
• Conceptualized, Developed, and Deployed ETL architecture using SSIS (shell integrated visual studio 2012, sql server 2012).
• Integrated warehouse wif Tableau server dashboards to provide business users greater insight into daily and monthly trade activity while reducing time to market for information.
• Project initially started as 8 week roadmap to build out 3 year data strategy aimed a constructing a data-as-a-service product offering valued at $53 million dollars; ended wif 11 month strategy effort to look at how teh use of emerging technology and data together can provide strategic corporate advantage.
• Teh roadmap provided architectural guidance, software engineering best practices, logical & physical data architecture, and infrastructure recommendations for a high velocity sensor data ingestion, storage, and analytics platform using Microsoft HDinsights (Hadoop), Microsoft PDW, and Microsoft Azure. An environment total expected to exceed > 1 petabyte in size in just over a year.
• Strategic advisor for re-development of globally distributed message brokering service dat ingested 53MB of data from over 250 sites across teh globe and leveraged SVM’s to generate maintenance schedules
• Total Client ROI - > 20%
• Responsible for delivering teh first practical application of teh internet of things architecture wifin teh oil and gas industry leveraging machine learning and data science techniques (Random Forest and SVM’s) to build predictive safety program and fleet travel optimization.
• Created and built up a dedicated Machine Learning group. Group now includes 12 full time delivery consultants encompassing several projects across industries. Effort also included prioritizing, designing, and in some cases actively working on developing IP.
• Created a new vision for Big Data Science dat encompasses building small teams of highly complementary skills (Data Science, Data Engineering, and Visualization). dis has enabled Clarity to scale its sale of Big Data projects. In order to scale my team of data scientists, me started a shadow program for our major projects where rising data scientists embed behind teh scenes wif a billing project team, and are given tasks while going through formal training. me’ve personally led two shadow teams so far, and teh program has since graduated 15 ready data scientists who had no previous experience wif Big Data or Agile and has proven to be a major success.
• Built all training collateral around Machine Learning, Python, Spark, Scala, Time Series, NLP, Consulting wif Data Science, etc. All of those training courses are now maintained and administered by rising analysts. dis training included a large canon of case studies from past experience.
• Developed a methodology to train rising data scientists, identifying skills and expectations at each level. More importantly developed a small group of rising analysts into manager / leadership positions. They are currently leading their own engagements wif little oversight. dis became teh precursor to teh shadow program.
• Changed recruiting strategy by working wif HR and recruiters to identify those most likely to succeed. Teh new recruiting factors encompassed a strong background in Math, Communication, and Creativity. dis also led to a change in onboarding training. In addition, established nontraditional connections at Northwestern University and University of Chicago to expand recruiting of promising but inexperienced graduate and undergraduate students.
• Developed prioritization of Machine Learning applications to be built out by our R&D team
• Designed and developed teh ACE offering (Advanced Customer Engagement) for Financial Services and Insurance. It encompasses leveraging a comprehensive view of all customers’ activities to enable personalization and automatically tailored business models.
• Introduced Spark to enable a new set of problems to be solved by our business. dis was a major initiative dat included training, sales, and development. We have been very successful wif teh sale and delivery of Spark based projects in teh past six months, covering a large portion of new data science projects. dis led me to win teh Innovator of teh Year award, and promotion as teh youngest TEMPPrincipal in teh company.
• Developed a new solutions centered on entity resolution and text mining dat enables teh finding of linkages across nodes in a graph. Completed teh go to market strategy for dis solution, and in teh process of training analysts on it while validating it in teh sales pipeline.
• Led, aided, and closed several data science sales across various industries. Those include strategy projects, complex machine learning problems, and Hadoop/Spark based projects.

Confidential

Managing Consultant and Chief Scientist

Responsibilities:

• Responsible for setting teh agenda for algorithmic delivery and optimization wifin engagement and product deliverables through teh implementation of IBM BigInsights and GreenPlum HD.
• Architected and delivered, multi-million dollar research effort for a fortune 100 client, dat cut channel specific fraud rates by over 79% using anomaly detection; saving an estimated $24 million dollars annually, using IBM BigInsights platform, Greenplum Database (v4.2), and R(MapReduce).
• Manage daily functionality of research and architecture teams; working wif engagement partners to define projects goals, scope, and deliverables.
• Established track record of successfully employing novel Machine Learning (ML) approaches to automatically discover insights from high-volume, high-dimensional temporal data (e.g., log records from computer systems, feeds from social media, dynamics of neural networks); designing interactive visualization tools for data/system analysis; and leveraging teh gained insights to automatically determine or guide management policies for complex systems.
• Responsible for end to end technical delivery of Enterprise Stress Testing program for a fortune 100 insurance and financial services client; Project included modeling program development, design of program technology architecture and topology, and econometric model delivery.
• Provided technical oversight to fortune 100 insurance and banking client on automation of regulatory reporting platform; reducing time of notice: to filing from 90 days to 45 days.
• Conceptualized, designed, and implemented enterprise wide data archaeology program for a fortune 100 banking/insurance client; dis allowed teh client to provide more transparency in analytical decision making; thus improving FDIC supervisory status.

Confidential

Sr. Manager

Responsibilities

• Management and accountability for teh day-to-day administration of a 36 node Hadoop cluster containing over 300TB of data, using Flume, Sqoop, Hive, HCatalog, Pig, and a Hortonworks distribution based HDFS architecture for Fortune Magazine’s no. 2 most promising company in America.
• Architected and implemented proprietary underwriting system dat enabled channel specific, rules and underwriting models to be designed, tested, and deployed in a deliberate manner wifin a controlled environment using GreenPlum DB (v3.3.7) and CEP.
• Led highly skilled parametric modeling, NLP, and machine learning teams in teh conceptualization, development, and enablement of various advanced statistical analysis, including scorecard development, logistic and linear regression, sentiment/funnel analysis, fraud detection, and text simplification.
• Oversaw teh establishment of data quality standards, data source stability, and teh establishment of company-wide data definitions, in accordance companywide standards.
• Created alignment between UK and US judgmental underwriting and decisioning platforms through strategy and application review and deployed a big data solution dat increased analytics velocity by 400%
• Mentored, developed, and lead a team of 5 big data developers and architects in teh full scale, enterprise-wide deployment of distributed systems using Hortonworks HDP (1.1 and 2.0) and GreenPlum DB (v3.37)
• Primary source of contact and integration for data vendors, including credit bureaus, social media (fliptop, gnip, datasift), weblogs providers (adobe, google), and fraud detection data.

Confidential

Portfolio Data Analytics, Manager

Responsibilities:

• Performed model validation and back testing, including K-S statistic, lift charts, ROC, tests for multi-co-linearity, and out of sample validation.
• Created analytical frameworks and controls to evaluate mortgage servicing unit performance through teh use of numerous types of business intelligence applications, including SQL Server 2005/2008, and SAS Enterprise guide v4.3.
• Created mortgage risk scoring dat measured risk attributed to various sources including borrower credit; current and future home value; borrower’s income stability, motivation to pay, and ability to afford teh home; and investor exposure through teh use of Monte Carlo Simulation.
• Identified business trends and tendencies used to develop and analyze KPI’s, KRI’s, and SLA’s and presented those findings to multiple stakeholders including, C-level management.
• Developed and maintained Monthly Performance Expectation Path models. These models forecast loan level performance of teh entire portfolio by estimating probability of borrower payment, foreclosure, REO, third party sale, short sale, modification, charge-off, paid in full, and bankruptcy, as well as gains and losses from liquidation, increasing security performance.
• Served as business analytics subject matter expert focused on conceptualizing, developing, and implementing actionable analytics aimed at increasing efficiencies across multiple layers of teh Capital Markets group.
• Managed, developed, implemented, and maintained teh new “Stop-Advance” model for scheduled remittance MBS deals using SSRS, SAS, and SSIS, having an estimated cost of funding savings of over $24 million dollars; received teh Center Stage award for outstanding contribution to teh firm for work associated wif dis project in Q2 2011 using layered MCMC and logistic regression models.
• Collaborated wif multiple internal business partners to develop benchmarks used to measure operational performance and support operational goal achievement bonus payouts.

Confidential

Sr. Solutions Architect

Responsibilities:

• Built complex, custom data management utilities (ETL processes, stored procs, Applications etc.) for various types of investment vehicles including mutual funds, hedge funds, and distressed debt portfolios using SQL server 2005/2008.
• Performed data administrator duties including monitoring of daily ETL processes, monitoring of SAS environments, workflows, and teh review and reconciliation of data concerning outgoing and incoming activity.
• Served as company consultant on teh implementation of reporting platforms for clients receiving market data. Responsibilities included overseeing data migration and integration, platform implementation, and training end users on GUI features and program processes.
• Provided seamless integration of various reporting platforms and programs, reducing potential user errors, increasing cost savings, strengthening data integrity, while increasing efficiencies across multiple business projects for contracts of $500k+.
• Led contractual negotiations wif external web services based data providers including IDC, DTCC, Thomson-Reuters, and Bloomberg.
• Performed data integrity projects and analysis for cash flows, contractual obligations, and multi-currency revolving debt instruments.
• Analyzed market trends for alternative investments including syndicated bank debt, hard and soft commodities, and mortgage backed securities (GSE’s, Private Label, RMBS, and CMBS) to insure data integrity and model performance.
• Tracked and reconciled data discrepancies and managed data exceptions for hedge funds, mutual funds, and institutional investors.