Robert Weyrauch

Cell: 480-***-****

https://www.linkedin.com/in/rweyrauch

adblxv@r.postjobfree.com

Summary:

Skilled technical leader and practitioner of data science with 20 years experience. Seeking a Principal Data Scientist position where advanced analytics and machine learning can help drive change. Skilled at setting strategic direction, partnering with domain experts and clearly articulating technical concepts appropriate for the audience. Deep experience in applying statistical modeling to achieve business objectives on schedule and on budget. Fosters a spirit of friendly collaboration where innovation, insights and evidence improve business performance.

Professional Experience:

Northern Trust – Tempe, Arizona

2018 - Current

Vice President, Performance Monitoring and Analytics

(Aug 2018 – Current)

Lead an analytics team focused on improving global infrastructure stability through problem solving skills and data driven root cause analysis of system failures.

Leveraged combined on-shore, off-shore, and near-shore teams.

Provide technical leadership, coach and mentor team members in relevant data science methods and tools including:

Applied natural language processing (NLP) on ticketing system data (ServiceNow).

Splunk and Elastic Stack for log analytics (6 TB/day).

Anomaly detection and time series forecasting.

Big data solutions including Cloudera Impalla, Hive, HDFS.

Early Warning Services, LLC – Scottsdale, Arizona

2004 - 2018

Senior Data Scientist, Data Science

(Jan 2017 – Aug 2018)

Fraud strategy optimization for the launch of peer to peer payments application for retail banking.

Managed multiple projects to meet deadlines while providing training and mentoring to junior team members.

Technical writing and presentation of findings to internal executive team, advisory committee and federal regulatory agencies.

Identifying data quality anomalies in time series data in near real time to minimize adverse business impact.

Led initiative for first company Open Source software contribution (2017).

Enterprise Information Manager, Enterprise Architecture

(Dec 2010 – Jan 2017)

Developed small, highly talented team focused on data science engineering, automated enterprise data flow integration and feature engineering.

Our solutions made it fast and easy to capture insights in one place, enabling informed, data-driven business decisions.

Conceived, rapidly prototyped and implemented the enterprise data lake combining complex data sets in excess of ~2 Billion data points per day.

Enabled unprecedented data insights by championing and implementing the first Hadoop cluster.

Saved the company $200k annually while improving accuracy by automating manual data handling at ingest.

Enabled real time data processing and reduced system overhead by replacing cron’ed directory polling with event driven message topics.

Led efforts to develop a universal ETL engine enabling automated data quality monitoring through statistical inference.

Manager, Statistical Analytics

(Jan 2008 – Dec 2010)

Provided leadership for new analytic products from concept to requirements to rapid prototyping.

Led initiative to leverage link analysis as a financial services industry fraud solution framework. This included strategic direction on concept, vendor selection, evaluation criteria and serving as a subject matter expert on internal data sources.

Collaborate with product teams in development of link analysis integrated statistical model of fraud risk.

Led development and implementation of transaction scoring models (participant model) resulting in an average 36% return rate providing ca. $508 million in incremental returned item warnings per year.

Presented analytic findings to advisory committee consisting of senior bank executives, as well as industry user conferences.

Senior Statistical Analyst, Statistical Analytics

(Jan 2006 – Jan 2008)

Provided leadership in building the company's analytics team, data store and analytics roadmap.

Led hiring, coaching and career development of top talent.

Researching, negotiating and purchasing software / hardware for analytics environment.

Establishing department best practices.

Designed, prototyped, developed and deployed predictive models (enhanced returns) resulting in a 101% increase in target event rate with a 5% reduction in warning volume. These warnings represent ca. $550 million in risk annually.

Researched and negotiated software contracts for analytics environment.

Implemented enterprise database integrating 10 TB of complex data sets in support of analytics initiatives.

Developed approximate string matching methods implementing customized edit distance algorithms to classify identity and address fraud.

Data Analyst, Statistical Analytics

(Sep 2004 – Jan 2006)

Founding member of decision science group responsible for in sourcing predictive model development and implementation.

Responsible for all stages of development: research and documentation of complex, existing data sources and processes, target definition, model development, model performance validation and advanced analytics.

Automated extraction, transformation and loading (ETL) of disparate sources and formats, along with requisite data hygiene and validation.

Defined requirements for and championed effort to establish a common data warehouse.

JP Morgan Chase – Tempe, Arizona

Sep 1999 – Sep 2004

BI Developer - Internet Servicing Group (Business Information Management)

Awarded over 10 awards for superior performance.

Analyzed customer behavior patterns to drive a sustained 51% increase in web page usage, thereby reducing customer service costs.

Extensive SQL experience including Oracle, MS SQL Server, and DB2.

Sunvest Financial Corporation – Mesa, Arizona

Oct 1996 – Jun 1999

Residential Loan Officer, Branch Manager

Developed and maintained automated marketing program used to extract customer loan program information from legacy Dbase 3 database.

Education:

Master of Science Information Management, Cum Laude, (May 2003)

Arizona State University

Bachelor of Science, Cum Laude, (May 1998)

Arizona State University

Docker fundamentals

Docker

Elasticsearch engineer series

Elasticsearch

Splunk user training series

Splunk

R programming

DataCamp

Data analysis in R, the data.table way

DataCamp

Data visualization in R with ggvis

DataCamp

Machine Learning

Coursera

Data scientists toolbox

Coursera

R programming

Coursera

Mixed Models Analyses Using SAS

SAS Institute

ANOVA, Regression, and Logistic Regression

SAS Institute

Applied Analytics Using SAS Enterprise Miner

SAS Institute

Predictive Modeling Using Logistic Regression

SAS Institute

Data Mining Techniques: Theory and Practice

SAS Institute

SQL Server 7.0 Database Design and Implementation

Microsoft Corporation

Keywords:

R, AI, SAS, clustering, supervised and unsupervised learning, artificial intelligence, machine learning, deep learning, simulation, mathematical modeling, logistic regression, statistics, anomaly detection, time series analysis, public speaking, prototyping, RFP, POC, vendor negotiation, contract negotiation, data visualization techniques, Tableau, D3 widgets, Bash shell scripting, DOS scripting, Docker, CRON, RPM, Perl, mentoring, version control, GIT, Jira, Confluence, Splunk, ELK, YAML, Markdown, JSON, REST constructs, HTML, relational databases (DB2, MS SQL, Oracle, etc.), ERD, data models, data flow diagrams, NoSQL, Apache Hive, Pig, Hbase, Lucene, Cassandra, Kafka, Big Data constructs, inferential statistics, descriptive statistics, feature engineering, model management, scorecard development, stochastic processes, signal processing, Bayesian analysis, Monte Carlo, Python, data.table, ggplot, plotly, forecasting, zoo, xts, rmarkdown, shiny, curl, caret, neural networks, decision trees, random forest, natural language processing, reinforcement learning, imputation, social network analysis, sentiment analysis, edit distance, fuzzy matching, collaborative filtering, probability, game theory, constrained optimization, Enterprise Integration Patterns, data munging, Microsoft Office, Excel, strategy, problem solving, Dataflux, MongoDB, Informatica, CDC, data warehouse, data marts, operational data stores, enterprise analytics, Microsoft SSIS, Oracle PL/SQL

Certifications:

SAS Certified Predictive Modeler

SAS Certified Base Programmer

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