Building an end-to-end AI development platform that focuses on local AI development. For those customers that care deeply about security and privacy we are enabling them to develop AI without the cloud.

• Conceived and led the zero-to-one product strategy and execution for Alteryx Copilot powered by Generative AI. Guided team from idea to beta rollout to customers in less than 4 months. This product enhances user productivity in building analytics workflows with Alteryx's no-code Designer Desktop app.• Defined strategy and led execution of MLOps features in Alteryx Machine Learning. Delivered the 3 high impact features of no-code orchestration, scheduling, and governance of machine learning workflows geared towards less technical personas, in less than 6 months.• Guided cross-functional teams to improve user experience in Alteryx Machine Learning, reducing our overall workflow from seven steps down to three. Resulted in a 25% increase in user funnel completion during the Alteryx Cloud trial program.• Led initial research efforts around AI & ML governance for Alteryx. Incorporated AI &ML governance into product development efforts, ensuring adherence to best practices in product development and deployment.• Serve as the primary liaison for internal and external stakeholders, communicating product vision, milestones and deliverables to foster strong relationships and effectively manage expectations.- Lead 1:1 qualitative feedback sessions with customers to gather insights and feedback on products, facilitating iterative product improvements that aligned with user needs.- Play a key role in product positioning and go-to-market strategies, leveraging market research and competitor analysis to identify opportunities, increase market share, and drive revenue growth.

• Led product management efforts for all internal AI and ML powered data products aimed at solving business challenges for our Sales, Marketing and Customer Success teams at Alteryx.• Spearheaded email marketing campaign product, powered by ML, that increased email open rates from 7% to 21%.• Led A/B testing initiative for our internal data science teams, creating a testing and measurement plan for all data science products. Allowed us to run at least 1 experiment/month to improve data product development.- Led numerous demos of no-code AutoML product, Alteryx Machine Learning, to assist Alteryx Sales team in customer conversations.- Spearheaded 3 internal machine learning use cases of Alteryx Machine Learning (AYX ML) across our HR and Finance teams to raise awareness internally of AYX ML, and provide marketable assets to our Product Marketing team.

As the Data Insights Product Manager I supervised a team responsible for delivering decision support products using machine learning and AI based algorithms. -Working with business users to derive a shared vision of how a data product will solve business problems.- Build outcome driven roadmaps to provide stakeholders visibility to product strategy.- Conduct stakeholder interviews to understand user behavior and workflows to improve data products for our internal business teams such as Warranties, Vehicle Lease Inventory and Engineering.-Assembling cross functional teams so that we can define data product goals with a measurable impact on the business use case.-Prioritize work to build data products in a fast and iterative fashion using Agile methodologies.- Align with engineering team to resolve capacity planning issues.-Manage data product lifecycle via KPI development and user feedback.-Serve as a data and product 'evangelist' within the company to help improve adoption for existing data products, as well as generate excitement to spur additional product discovery opportunities. -Communicate the impacts of data product development to GM and VP areas outside of my ‘home’ department (i.e. IT), including finance, sales, and after sales.-While only in the role for a short time (~ 7 months) , my team was able to deliver 3 machine learning powered data products to our business units.

In my role as a data scientist at Mercedes-Benz USA:- I have led/am leading a number of data science projects related to topics such as anomaly detection in warranty records, text analytics of repair order comments and time series prediction vehicle lease returns.- I have also collaborated on a data science use case aimed at predicting customer churn using machine learning models and leading big data technologies such as Apache Spark, Azure Databricks and H2O.ai- Provide reviews of statistical methodology, code used to generate machine learning models, and further analytical support for outside consultants- Participate in data migration projects aimed at moving MBUSA data from existing data warehouses to a Microsoft Azure cloud platform.

Shearwater Analytics was a statistical consulting business aimed at providing cutting edge data science solutions to a range of research domains. I decided to no longer pursue contracts due to time limitations. Web page and LinkedIn profile no longer maintained.

In my role as retail analytics manager:- Led analytics and reporting efforts on Acosta's Dynamic Retail program. This was the first program rolled out by Acosta that aimed to use advanced analytics to dynamically route field reps to stores to improve sales margins across 1000s of CPG products.- Provide analytics advice and guidance to other Acosta data science teams.- Brief upper level management and executive team on Dynamic Retail program results weekly, reporting on business critical KPIs and resultant lift of Dynamic Routing program. - Provide corporate training opportunities in R programming for our more junior analysts- Create custom data visualizations and storytelling materials, synthesizing core findings and results- Data cleaning and munging

Developed Ornithology course that included both lectures and lab.

My primary duties include statistical modeling of datasets that span large geographic areas over multiple years. During my time at Audubon I have implemented hierarchical Bayesian models, machine learning algorithms and used parallel processing to reduce processing times.

Serve as the lead data scientist for a project aimed at assessing population trends of Greater Sage-Grouse with the overall intent being to provide conservation and management recommendations for this highly imperiled species

Led a bird banding team consisting of fellow graduate students and paid undergraduate assistants charged with collecting avian census data contributing to a 50+ year study of avian community turnover at Hutcheson Memorial Forest.

Performed survey of shorebird communities within the Jamaica Bay National Wildlife Refuge