Leading our API strategy for the Commercial Real Estate (CRE) Business. Oversee development of product integrations, API products, and internal services, notably the MA CRE knowledge graph. Build relationships with our customers to understand their needs and communicate goals, strategy and roadmaps to product, engineering, sales, and support teams. Advise on internal infrastructure strategies to accelerate product development and empower data analytics. Foster partnerships with firms across the industry.

Responsibilities:Develop new products in Commercial Real Estate by managing Prototype and MVP projects. Work closely with business development and product strategy teams to define product specifications, go-to-market plans, and success metrics. Lead iteration planning meetings, stand-ups, and methodology discussions with our data science team and plan stories and iterations with our software engineering team.

Responsibilities: Develop Geospatial microservices in Python and AWS for the Commercial Location Score platform. Support corporate strategies by evaluating partner data and socializing ideas with research and product teams.Achievements: Provided product management support to the small engineering team by adopting and maintaining XP/Agile best practices. Led daily standups and weekly Iteration Planning Meetings to maintain clear feature development path and acceptance criteria. Alpha product was ready for client trials 4x faster than historical development times.

Responsibilities: Lead product analyst for API products and cloud migration. Utilize AWS Lambda, Python, and API Gateway to create APIs to support internal operations. Provide measures of response times and error rates for API endpoints to determine viability of backend services. Advocate the use of APIs to expose company wide data assets to new and existing clients.Achievements: Emphasized value of API products by developing R Shiny Apps within weeks, leveraging internal APIs to show the short time to market advantage. Determined application feature implementation by leveraging response time metrics to improve user experience.

Developed data products focused around API. Implemented AWS cloud technology such as Lambda, S3, Redshift, and Aurora, to support internal data operations.

Achievements: Developed and deployed automated Data Quality Control systems through R and SQL to reduce data errors in products. Took the initiative to take over an old, inefficient process for a high value product and developed a faster (99% faster) and more scalable process. Daily Tasks:Investigate data related issues reported by clients. Maintain a Salesforce queue of client cases. Communicate with several different teams including Data Production, Data Quality Control, Client Support, and Research to resolve client issues, development new features, and improve internal processes. Build data pipelines to process data and support model implementation.

Responsibilities: Update minimum wage data for public work projects in Excel and Oracle databases using SQL, producing ad hoc economic reports that analyze the impact of new state senate and congress proposed policies, and presenting economic analysis with data visualizations and summaries in Excel to Research Managers.Achievements: Developed an automation process for the minimum wage and CPI publications produced by the department using VBA and VBscript. Reduced the man hours required by 90%.

Clean raw data collected from survey using R, built statistical cluster models to demonstrate storerelationships, and presented recommendations in Excel about a minimized cost strategy to design teams and senior management in Visual Merchandising and Brand Operations.

Helped students implement newly developing software called OSSIE (SCA-Based Open Source Software Defined Radio). Documented procedures for installation and use. Recorded any bugs in the software. Tested signal processing hardware with the software