Current/Recent Clients & Projects: - Private, Large Manufacturing Company: Data Enablement & Capabilities Advisory - Private, Large Manufacturing Company: Data Executive Coaching - Private, Small Manufacturing Company: AI & Data Executive Board Education- Non Profit, Mid Sized Youth Mentorship Org: Data Maturity & Literacy Assessment, Sr Leader On-boarding- Pre-Seed, Construction Data Services Company: Tech Stack & AI Approach Audit

•Build an organization for 850+ aspiring and practicing data scientists to apply their knowledge and exchange industry knowledge.•Organize and orchestrate data science competitions for 200+ students across the country.•Showcase talent on a level playing field for participants from 22 institutions across the Midwest.•Work with C-Level non-profit leaders and government organizations to spread awareness.•Lead hands-on training sessions with actual code, accurate data, and real problems.•Partner with other existing analytics organizations (MinneAnalytics, MUDAC, StatCom, etc.)

•Design and teach a new course "Data Stores & Feature Design" for Fall 2023•Dive into specialized data formats, such as time series, geospatial data, semi-structured and the data management systems and considerations required to load and extract information from them. •Leverage both creativity and context to design highly impactful features for machine learning. •Compare and contrast the conceptual designs of relational, data warehouse, NoSQL, and other data systems. •Expose students to high-level concepts, such as data governance, data lineage, and metadata management.

•Lead a technical organization of 17 members that work on the core of the flagship measurement product, which accounts for more than 7% of company revenue. •Delivered structured and scaled data science and MLOps to enable hitting product growth milestones; this resulted in 60% growth in client instances. •Pushed for Professional Services Data Science team to enable strategic consulting to drive Ovative to learn faster in tandem with our clients on unsolved marketing measurement problems facing the industry. •Structured data science into four functional teams to accommodate internal demand while keeping it a cohesive data science organization. This led to142% team growth with 0% attrition over the course of 11 months.•Participate in 3-4 direct external client engagements a year ranging from 200-500k; these engagements allow Ovative to develop expertise, perspective and explore potential productization of results. •Collaborate with senior leadership from Business Development, Client Services, Strategic Consulting, Data Engineering, and more to drive critical business objectives end to end.

•Served as a technical leader for 16 data scientists that produced four enterprise products across several internal departments. Users of these solutions included Marketing, Pricing, Supply chain, and more.•Worked alongside a global team of 20-26 data scientists to drive 14 different projects for various internal users within General Mills. This work resulted in delivering $118 million in value for the company.•Collaborated with senior stakeholders (VP, Director, Senior Director) to gather requirements, monitor project progress, and roadmap for future improvements.•Evaluated and implemented best practices, standards, and project lifecycles for short-term projects (6-12 months) and evergreen solutions.•Ran enterprise analytic leader forum, bringing together 10+ diverse functions to discuss how data can be leveraged and the roadmap for future capabilities.•Plan migrations of 25+ analytic workflows to the cloud, cataloging dependencies and needed enhancements.

•Planned and allocated proper resources for four evergreen enterprise projects set to deliver 100+ of million in value. This involved gathering requirements, developing the project roadmap, and determining staffing needs to complete the initiatives.•Shifted data science team to operate within product teams alongside a central data science team to solve larger scope challenges. This allowed the organization to improve in cross-team training as well •Managing a data science team of 6-8 employees. Responsibilities include hiring, employee development, and conducting performance reviews.•Provide enterprise perspective and expertise on AI to all cross-functional peers and leaders

•Mentored six different coworkers on data science techniques, best practices, and company procedures.•Drove the adoption of agile methodology and project management tools to improve efficiency across the data science team.•Implement version control standards, code standards, unit testing, and continuous integration

•Assisted in creating vision, framework, and project prioritization for a shared service data science team.•Evangelized data science to senior leaders by providing comprehensive analyses and recommending solutions to complex business problems using data from internal and external sources.•Enrich existing data through various methods such as using APIs, leveraging 3rd party vendors, and building web scrapers.

•Hired as the first data scientist within General Mills to build out best practices, determine use cases, and construct cross-functional partnerships with stakeholders.•Applied machine learning practices to classify data into marketing segments and detect anomalies. Conclusions from this data resulted in optimizing efficiency within various General Mills groups.•Detangled and transformed the wide varieties and veracity of CPG data into actionable insights.

• Identify and present potential solutions to critical marketing data architecture• Liaison departments to provide customer and prospect data for marketing campaigns • Review with IT architects that all marketing infrastructure specifications and requirements are met• Standardize and optimize reoccurring processes to provide efficient and accurate information • Plan around anticipated regulation and guidance changes for marketing data privacy

• Provide deep analytics around pricing initiatives using several different DBMS platforms• Create dynamic competitive indexing, strategic pricing insights for executive leadership• Technical teaching and instruction

• Built and documented robust and dynamic analytic tools using Excel, VBA, and databases• Created and automated easy to maintain, high precision, custom reports• Developed technical user guides for in-house investment tools

• Deployed new fee schedule for Investment Management and Trust accounts• Described book of business impact to 135 investment professionals • Communicated software developers to describe project usage needs and technical issues• Investigated discrepancies on a database of over 2,000 accounts

• Analyzed and forecast fixed income security losses using Excel and pivot tables• Researched changing market legislation to anticipate potential impact to current and potential holdings• Independently created a security cash flow analysis model within Excel

• Strengthened ability to analyze situations and solve problems, all while using Mandarin Chinese