Gordon Scarlett

CROSS-FUNCTIONAL DATA PLATFORM IMPLEMENTATION

• Implemented an enterprise data virtualization platform by first, socializing the concept and desired solution across technology and business leadership, creating consensus, procuring governance approvals (technical, financial, data) and funding to build the team to implement Denodo Data Virtualization at Schwab
• This allowed us to avoid the investment in time and capital that would have been expended had our data deliver strategy continued to rely on moving data to a centralized location prior to making it consumable by our business partners and applications
• The success of this implementation accelerated access to governed, discoverable data aligned with business use cases and consumption patterns, centralized once disparate business logic and rules, accelerated decision making and reduced decision risk
• Denodo is currently being used enterprise wide to address our need for a holistic, governed view of our disparate enterprise data
• Built and lead a team of architects, developers, and analysts tasked with maximizing the value of internal and external data by aligning its accessibility with the business’s informational needs around strategic decision making across all lines of our business model, Asset Accumulation, Investment Management, and Back/Middle Office operations
• Implemented a business intelligence platform that incorporated artificial intelligence (AnswerRocket)
• The strategy and driver was to eliminate the technological barriers between insights and business users by allowing them to interact with data in Natural Language (spoken English)
• Transformed the business requirements development process by increasing discussions between architects, developers and the business with a renewed focus on addressing questions that the business user wishes they could answer
• By focusing on identifying the data that would answer those questions and the systems or sources of the necessary data, we were then able to not only address functionality deficiencies but allow business partners to reduce their universe of unknowns and improve their business processes and decision making

MERGERS AND ACQUISITION DATA INTEGRATION ACCELERATION

• Accelerated the integration of data from several acquired Managed Accounts firms resulting in improved delivery of a managed accounts product strategy to our clients thereby improving our competitiveness in the marketplace and enabling market share expansion
• This approach enabled immediate productivity while buying us time to develop our strategic enterprise managed accounts platform
• Acquisitions included TD Ameritrade, Wasmer Schroeder, and Thomas Partners

DATA VIRTUALIZATION CENTER OF EXCELLENCE

• Faced with the challenge of the expanded utilization of Denodo across the enterprise, created a group to support experienced or new developers by centralizing the establishment of coding best practices, use case evaluation, code reviews, etc
• This move ensured that for those challenges where Denodo was being evaluated as part of the solution set, Denodo’s SLA aligned with that of the business’ use cases, coding was consistent and easily transferable, and utilization of the tool aligned with its strengths and our organization’s ability to support it
• This entity allowed us to avoid the mis-alignment of the tool with business challenges hence eliminating avoidable risks associated with potential under-performance or platform failures that could critically impact the business

TECHNICAL DATA GOVERNANCE

• Evaluated an existing technical data governance process that relied heavily on administrative activities that “checked the boxes” but had little connection to mitigating risk around data sources, storage, and accuracy
• By implementing a Center of Excellence (CoE) and an operating model that focused on those activities where a direct connection could be drawn to the purpose of the technical aspects of data governance, we were able to increase developer cooperation on the activities that were dependent on their participation and improved our ability to reduce data risk and address audit concerns
• This approach enabled the enrichment and usability of our data catalog and data lineage documentation which provided the visibility into our data universe that enables increased data accuracy and best source identification for CDEs
• It also enabled the ability to implement governance adherence across all of Schwab Wealth & Asset Management Engineering (10+ Scrum Teams)

SCHWAB ACCOMPLISHMENTS

• CEO Award 2019
• Key Contributor Award 2018, 2019, 2020
• Keynote speaker at InvestOps USA Conference (Data Virtualization) 2019
• Schwab Technology Services Big Ideas and Bagels presenter 2019
• Schwab Technology Forum presenter 2019

• Developed and implemented an analytics roadmap as well as a strategy to align IT's Data Integration and Warehousing team with the business' Business Intelligence Team to enable the ability to address more sophisticated and perplexing challenges
• Applied statistical and machine learning methodologies to persistent business challenges like advisor propensity to increase/decrease assets, attrition analysis, asset build analysis, actionable dynamic segmentation and profiling of advisors for more productive/profitable targeting by our external sales team
• Developed a segmentation model utilizing R that identified advisors with high propensities to both acquire our funds and to engage with our salesforce by including variables that were not attainable with previous methods
• This was due to the degree of feature engineering and data analysis required to identify variables as viable and delivered thousands of advisors that had been previously overlooked.

• Developed a strategic roadmap, tactical plan, and budget to consolidate a geographically dispersed data environment consisting of data warehouses and teams utilizing BI suites from Microsoft (SQL Server, SSIS, SSRS), Oracle (OBI, MySQL), and Informatica
• M&A activity halted implementation.

• Lead a team of data architects, Informatica developers, and MicroStrategy developers tasked with consolidating and maximizing the value of operational data by aligning its accessibility with the business’s informational needs around strategic decision making.

• Developed a framework for a marketing analytics function within the Marketing department and designed and developed a data infrastructure with Microsoft SQL Server that integrated previously disparate data sources in order to better analyze our customers’ behavior, target effectively, and analyze our marketing efforts.

• Applied statistical methods and principles utilizing SAS in the analysis of direct marketing and media campaigns in order to determine the effectiveness of various offers and the profitability of the campaign by measuring response rates of the targeted audience as well as their eventual product selection, balance levels, service usage, and attrition rates.