Have a question about my analytics leadership experience, technical expertise in Python and machine learning, or approach to driving product innovation through data insights? I’d love to discuss how my strategic analytics background can deliver measurable business growth for your organization.
- All
- Background & Experience
- Current Focus & Career Goals
- Executive Communication & Cross-Functional Collaboration
- Leadership & Technical Expertise
- Problem-Solving & Innovation
- Product Analytics & Business Strategy
I’m a seasoned analytics leader who leverages data insights to align cross-functional teams toward shared goals. With infectious enthusiasm for analytics, I combine technical expertise in Python, SQL, and machine learning with executive communication skills to transform complex data into strategic business insights that drive product innovation and measurable business growth. My journey wasn’t linear—I started with a Biology degree, built and ran a web development company serving 100+ clients including a Fortune 500 company, then transitioned into analytics leadership roles including the U.S. Census Bureau.
I’ve worked across government (U.S. Census Bureau), consulting firms, industrial and engineering firms, retail, and Fortune 500 enterprises (AMD, MosaicCo). My entrepreneurial background serving 100+ clients gives me insight into how different business sizes and industries approach data challenges, from local businesses to large-scale organizations requiring enterprise-level analytics solutions and data governance frameworks.
As Lead User Analytics Analyst, I led user analytics initiatives that directly influenced executive decision-making. I diagnosed a critical indexing error that made 215 key pages invisible to search engines, resulting in a 68% increase in new users within one month of the fix. I also managed quarterly analytics frameworks synthesizing multiple data sources and engineered processes that identified $1.56M in potential annual savings through strategic software consolidation.
My leadership philosophy centers on developing people first through active mentoring and coaching. I understand each team member’s career aspirations and create opportunities for professional growth. Cross-functional team leadership requires aligning diverse stakeholders around shared goals through data-driven storytelling. I ensure all voices are heard and lead by example with healthy work boundaries. At the Census Bureau, I successfully aligned development, product, and executive teams by tailoring business cases to each group’s objectives.
My technical expertise includes Python and R for data science and statistical modeling, SQL and JSON for data analysis and architecture, and machine learning for predictive analytics and feature engineering. I use Tableau, PowerBI, and Excel for data visualization, and I’m AWS Certified Cloud Practitioner with experience in cloud platforms. I also work with project management tools like Jira, Asana, and ServiceNow for cross-functional workflow coordination.
I hold an AI & Machine Learning Certificate from UC Berkeley and am currently pursuing my MS in Data Science at Colorado School of Mines. My experience includes statistical modeling, predictive analytics, and feature engineering for business applications. I understand both the technical implementation and the strategic business value of AI solutions. I partnered with a local wealth management firm to develop an AI retirement simulator leveraging probability and statistics for financial forecasting, demonstrating my ability to translate complex AI concepts into practical business applications. At the Census Bureau, I leveraged AI tools to accelerate JavaScript proficiency for developing custom analytics solutions, and I apply cross-validation and advanced statistical methods to ensure reliable model performance.
I start with comprehensive user analytics to understand behavior patterns, engagement metrics, and conversion funnels. At the Census Bureau, I engineered custom Python processes to extract user behavior patterns from URL parameters, creating cost-effective analytics solutions without expensive implementations. My approach combines quantitative user data with qualitative feedback to develop context-based product strategies that balance business objectives with user value.
I use data-driven frameworks that synthesize user research, market analysis, and business objectives into prioritized product roadmaps. My process includes stakeholder alignment sessions, impact vs. effort analysis for feature prioritization, and regular executive communication of progress. I break complex initiatives into phases with clear milestones and success metrics, ensuring product innovation aligns with measurable outcomes.
I establish data governance frameworks from the ground up, focusing on data quality, security protocols, and strategic planning for scalable analytics infrastructure. At Stanley Consultants, I designed enterprise data architecture that enabled full-cycle HR data reporting for recruitment, retention, and operations while implementing governance frameworks ensuring regulatory compliance. My approach combines technical architecture with business requirements to create sustainable data strategies supporting organizational growth, reducing manual reporting by 40 hours monthly.
I specialize in transforming complex technical information into compelling presentations that drive strategic decision-making. My approach involves understanding each executive’s success metrics, leading with business impact and ROI rather than technical details, and presenting solutions with clear measurable outcomes. At the Census Bureau, I presented quarterly customer voice insights to senior leadership that directly influenced product roadmaps and strategic planning across multiple departments.
I leverage data insights to create shared understanding across diverse stakeholders through compelling data storytelling. My approach involves understanding each team’s success metrics, translating technical insights into business value, and maintaining transparent communication about trade-offs and priorities. I use project management tools like Jira, Asana, and ServiceNow with detailed user stories specifying “who, what, and why” for each initiative, plus regular milestone reviews and structured communication channels.
I treat data infrastructure as a product to be ingested, not just a system to maintain. I actively track who uses these data products and for what purpose. At AMD, I set up a JIRA-based tracking system to monitor what teams we are serving. With dashboards, I enable usage monitoring: clicks, unique users, and note data insights are driving business decisions. This visibility enables communication of ROI and strategic alignment for executives, engagement trends for improved reporting, and implementation detail for technical teams.
At Stanley Consultants, I resolved a years-long HR data challenge where applicant and employee information were stored in separate, siloed systems. By identifying that unique applicant IDs could bridge the datasets, I proposed a simple custom field solution that enabled full-cycle workforce analytics for the first time. Working with HR and operations executives, I standardized the reporting processes, saving managers 40 hours monthly while unlocking strategic workforce insights that were previously impossible to access.
Innovation requires being open to how a problem gets solved. Stanley Consultants had deemed their database issue ‘impossible’ because it was not achievable through a standard system setting. I found the solution by shadowing the people doing the work and then defined the custom field solution. I applied that same mindset at FEMA, building a custom index to solve a complex statistical modeling problem and predict information that had previously been inaccessible.
I look for growth opportunities by combining market analysis with competitive intelligence. At Census, I did GEO work for AI (generative engine optimization). I optimized how information, like how to fill out a survey, could be found and understood by both humans and agents. At AMD, my focus has evolved toward preparing data for agentic analytics: building architecture and knowledge infrastructure that agents can actually ingest and act on, not just dashboards for humans to read. I am energized by data-driven outcomes that balance technical feasibility with measurable business impact.
I love my current MTS Data Engineer role at AMD building data infrastructure for a newly formed team. Within my first 60 days I deployed a Power BI Timing Metrics dashboard that scaled from 2 to 8 projects by month four, landing in the top 1% of AMD’s 4,000+ org-wide reports. I’ve architected normalized Postgres infrastructure, established cross-team governance and metrics standards, and built tooling that tracks real progress across multiple high-priority CPU programs.
When ChatGPT launched in 2022, I went back to Arapahoe Community College for Calc 2, Calc 3, and linear algebra to understand the math underlying these models. I’ve since completed graduate coursework at Colorado School of Mines, including probability theory and advanced statistical modeling. I stay connected through Women in Tech and MLOps Denver, and am grateful for mentors who sharpen my skills in AI thought leadership.
I’m energized by aligning cross-functional teams around shared goal. I thrive in roles that combine technical expertise in data science with product strategy, team leadership, and feature engineering. Clean data infrastructure is the foundation for organizational decision-making. My enthusiasm for analytics, paired with strong executive communication, lets me bridge deep technical work with strategic business planning.