Yvonne Edmonds Email and Phone Number

• Directed a team of 7+ senior-level data scientists and managers to deliver on-time actionable machine-learning solutions in the supply chain, business, and healthcare spaces. Projects include demand forecasting, predicting supply disruptions, customer attrition, financial forecasting, and optimizing oncology patient quality-of-care metrics. ML initiatives delivered over $10M+ in quantifiable value each fiscal year. Responsible and accountable for several KTLO projects that facilitate key initiatives and pharmaceutical distribution strategy.• Develops strategy to create, pilot, deploy, maintain, and extend ML solutions across business units and subject matters; champion and broaden knowledge of data science in a 70,000+ employee enterprise; hire and train top-talent in a non-traditional tech setting; standardize batch and streaming model training and serving protocols in a multi-cloud CI/CD MLOps environment.• Partners with consultants, 3rd party vendors, digital accelerators, and universities to accelerate innovation through collaboration and proof-of-concepts; benchmark; streamline hiring; evaluate new data sources and ML platforms. • Formed/leads a Data Science Community of Practice (CoP) to empower and connect 130+ data science practitioners and enthusiasts enterprise-wide to promote knowledge sharing, best practices, and collaborative learning in alignment with business goals and company vision of improving care in every setting. CoP offerings include an in-house website of data science resources, with pages on machine learning, code management, project workflow, cloud platforms, etc…; monthly meetings, including training, peer and external-led presentations, office-hours; a discussion forum; and access to SME’s.• Communicates machine learning initiatives to a diverse audience, including executive-level leadership, business stakeholders, and individual contributors. Translates organizational and technical strategy to initiative and delivery horizons

• Managed remote and in-person countrywide team of senior-level data scientists and business analysts to ensure on-time delivery of effective machine-learning solutions in a multi-cloud environment (MS Azure Databricks, Google Cloud Platform, Linux Virtual Machines, Snowflake SQL). Conducted weekly code and methodology reviews to provide guidance on statistics, error analysis, noise reduction, feature engineering, machine learning techniques and programming pipelines (Python (expert), Java (beginner), R (beginner)). • Responsible for technical deliverables of proof-of-concepts, minimum viable products, and production models for tactical and strategic projects in inventory management, competitive market dynamics, risk mitigation. Cost-benefit analysis of the value of ML projects at $10M+ per fiscal year. Projects utilize a variety of ML techniques, including statistical benchmarking, classification, regression, clustering, deep learning, linear programming, etc..• Liaison between Analytics team and Legal team on machine learning patent process. Role included identifying patentable projects, collations of patent submissions, presentation of patent ideas to legal team, dissemination of IP protection procedures to Enterprise Analytics team. • Organized an Enterprise Analytics weekly team meeting for 60+ attendees to foster engagement, provide project visibility, and brainstorming opportunities during work-from-home. Wrangled 10+ Enterprise Analytics university summer interns to promote productivity, enhance their summer experience, and convert a diverse talent pipeline to employment.• Upskilled data scientists on the use of statistic for analytics, object-oriented programming (Python, Java) to provide systematic and rigorous machine learning solutions for reuse in our shared code environment (Github). Advised and trained data scientists outside of my direct management chain.

-Built Fantasy Film Game, a web app that allows the player to design the film they want to see, recommends a similar Hollywood film, and predicts the profit from domestic ticket sales. The fantasy and Hollywood films compete on sales at the domestic box office. -Scraped movie box office and actor data, stored data in MySQL, and predicted ticket sales using regression in Python. Employed a similarity matrix to find a Hollywood film similar to the user’s input. -Developed front end using Flask, Javascript, jQuery and AWS.

-Analyzed datasets using Matlab and JMP to qualify and improve system performance, andvalidate system specifications. Designed and executed prototype acceptance tests.-Produced risk analysis, performance budget, and problem solving documents.-Defined requirements for software features. Provided advice to software groups onprioritization of features and bug fixes.-Collaborated with software, hardware, manufacturing, field support, marketing, and finance groups to deliver new software versions to the field. Drove and coordinated the delivery of system components to mitigate end-of-life risks.-Mainted tool health as tool owner for a prototype tool. Traveled in Asia and the US to support products at customer sites and manufacturing site.

-Performed a dark matter search as part of the Fermi Large Area Telescope Collaboration.-Utilized statistical techniques, including maximum likelihood estimation and bootstrapping,to search for a small signal in a large dataset, taking into account systematic errors andmodel uncertainties.-Analyzed calorimeter calibration and beam test data to improve the detector’s measurementof high energy radiation. Performed multivariate studies of detector response to photons andcontaminating particles.