πΌ Work Experience
IBM
π 09/2023 - 10/2025 π San Francisco, CA
My Role
π©π»βπ» Technical liaison to 9 accounts (5 of top 25 tech companies) for Generative AI and AI Governance platforms. Delivered client presentations, demos and POCs, designed and executed prospecting campaigns, developed architectures, and collaborated cross-functionally (Sales, Product Management, Customer Success, etc.) to identify revenue opportunities ($2M+ sales opportunities identified), co-create with clients, and accelerate sales cycles.
Key Accomplishments
β Drove $9M+ in software deployment and $2.4M+ in sales of Al and Automation products across enterprise, Fortune 500 accounts in technology and retail industries.
β Engineered and demoed proof of concept Al agent with custom integrations and tools (prompt engineering, Python, APls) for large tech company, leading to $200K+ in SaaS usage and services deal.
β Expanded software adoption at Fortune 10 retailer ahead of Enterprise Licensing Agreement, making Al and Automation portfolio 30% of total SXM ELA and over-achieving SaaS quota (105% attainment).
β Proved technical value in pre-sales and post-sales by delivering client demos and presentations, designing architectures, and developing proofs of concept of AI solutions that identified ~$2M in sales opportunities.
Technologies Used
βοΈ Generative AI, Prompt Engineering (IBM watsonx.ai, Python SDK for Inferencing)
βοΈ AI Agent development (Python, IBM watsonx Orchestrate)
βοΈ AI Governance and Responsible AI (IBM watsonx.governance)
βοΈ Salesforce (Sales Cloud, Dashboards)
βοΈ LinkedIn Sales Navigator
βοΈ ZoomInfo
βοΈ Microsoft Excel
βοΈ Microsoft PowerPoint
βοΈ Microsoft Copilot
BallerTV
π 06/2022 - 08/2022 π Remote, CA
My Role
π©π»βπ» 1st software engineering and 1st startup experience. Allowed me to learn a lot of new skills by getting my hands dirty and working with a variety of teams. Did backend development on the Engineering team, data analytics and engineering for Product Managers/Leaders, and software engineering and data-centric work with the Automation (Data Science) team.
Key Accomplishments
β Built scalable data pipeline in Ruby to clean, extract, and calculate statistics for 1 million games with Generative Al API integration to create custom headlines for subscribers, driving product engagement. This project was the pre-cursor to a GPT application.
β Designed dashboards with SQL and Redash to visualize travel cost metrics and asset tracking data, empowering product managers and leaders to make data-driven cost-saving decisions.
β Automated timely communication by programming a workflow that sends text messages to contractors via the Twilio API and Active Record (Rails) when work schedules change.
Technologies Used
βοΈ Ruby (Rails)
βοΈ PostgreSQL
βοΈ Git
βοΈ GitHub
βοΈ Jira
Bessemer Venture Partners
π 06/2022 - Present π San Francisco, CA
Key Accomplishments
β Selected as 1 of 20 fellows from 2,000+ applicants and 60+ finalists; portfolio company directly reached out.
β Engaged in entrepreneurship studies with founders and product leaders from the venture capital industry.
TE Connectivity
π 06/2021 - 06/2022 π Remote, CA
My Role
π©π»βπ» My 1st ever internship that opened the doors for everything that has come after. Learned the art of storytelling through data, the importance of cross-functional collaboration, and how to communicate technical topics to non-technical audiences. Worked on TE's Advanced Analytics team as part of the hub team/center of excellence for the company's Data Science and Analytics.
Key Accomplishments
β Analyzed deep learning forecast model results with Python Pandas and identified 1,000+ highly accurate parts making $300M+ in sales to promote adoption of cost-saving forecast model in presentations for C-suite executives.
β Developed Python automated fuzzy matching algorithm that improved accuracy by 50%, was adopted on 2 projects used by 5 departments, and maps predictions to actual sales for marketing campaign tracking.
β Implemented statistical randomization methodology with Python, SciPy for A/B testing, reducing manual labor and enabling marketers to accurately evaluate their campaigns.
β Created data pipelines to map Al predictions to actual sales data for campaign performance tracking.
Technologies Used
βοΈ Python (Pandas, SciPy, Matplotlib)
βοΈ SQL
βοΈ AWS (SageMaker, S3)
βοΈ Jupyter Notebooks
HalΔ±cΔ±oΔlu Data Science Institute
π 10/2020 - 03/2023 π San Diego, CA
My Role
π©π»βπ» Tutors were my lifeline when learning how to code, so I wanted to be the same for fellow Triton Data Scientists. I tutored DSC 20 - Programming and Basic Data Structures for Data Science (Python) for 5 terms (Fall 2020-Fall 2021 and Winter 2023) and DSC 30 - Data Structures and Algorithms for Data Science (Java) during Spring Quarter 2022.
Key Accomplishments
β Enhanced 500+ students' Python and Java skills in topics like object-oriented programming, recursion, and data structures by helping them understand assignments and coding logic during 4 weekly office hours.
β Reinforced lecture material through creating weekly quizzes, moderated the question and answer forum to resolve studentsβ issues, and contributed to the creation of programming assignments.
Technologies Used
βοΈ Python
βοΈ Java