I am a data scientist specializing in product innovation and new product development. I use lean software development and agile software development practices to get MVPs and POCs in-front of customers as soon as possible. I use voice of the customer and empathy to learn from the end users and customers about their journey maps, pain points and how AI/DS can make their lives better. I've mainly worked in cross-functional teams as the main data science lead and analytics lead working alongside product managers, UX/UI designers, architects, software engineers, data engineers, and professional services. The solutions I develop have been for both internal customers (process efficiencies) and external customers (NPD). The data science solutions and ML models were actively developed with our beta customers hand-in-hand for quick iteration and feedback and always focused on the customers first.I've worked mainly in the asset performance management space (dealing with CMMS), IoT space in an effort to push companies into the predictive and prescriptive maintenance spaces. I've also done projects in data migration, and marketing analytics.Tools: SQL, Python, experimentation, machine learning, lean, agile, unsupervised machine learning, supervised machine learning, generative AI

Contractor for a large internet company based in the San Francisco, CA bay area for their data science team under their sales and advertising division within the global business organization. I consider myself a business/support data scientist, where I apply data science and machine learning to increase our revenue by augmenting the capabilities of our sales team. I created multiple dashboards to provide weekly and on-demand updates on business and technical KPIs (e.g. correlations, RMSE, recall, precision) for ML models in production that highlight high-revenue accounts for sellers to pursue. This has involved me translating multiple notebooks (jupyter, R, python) into SQL. These dashboards have great visibility within the organization, consumed by both technical (data scientists and PMs) as well as business (sales and ad team) stakeholders at senior levels.Took over an existing experimental study in partnership with the international growth sales team, and implemented improvements to study designs, translated the original R scripts into Python for increased accessibility within the DS team, as well as performed an in-depth analysis on previous year's studies.Tools: SQL, Python, dashboards, experimental design, machine learning, regression, data visualizations, data storytelling, KPI creation and tracking, R, jupyter notebooks, workflows

I spearheaded 2 corneal biomechanics research projects in collaboration with 2 ophthalmologists in a start-up lab with the purpose of improving clinical outcomes in corneal transplant surgery. I published my findings in 4 journal articles and presenting 10 research posters in 4 conferences.I designed and built several custom experimental materials testing platforms using fundamental engineering principles to simulate steps in corneal transplant surgery and identify potential sources of mechanical trauma.To analyze the experimentally collected materials testing data, I translated mathematical models of elastic and viscoelastic theory into MATLAB scripts. These were used to analyze and calculate mechanical properties of the cornea. Code was validated against published mechanical data of artificial and biological materials.I conceptualized, developed, and executed all research designs. I also performed all statistical analysis for the research projects. I ensured correct experimental and control groups were considered for each treatment type, as well as sham groups to account for protocol methodology (important to isolate results between a control treatment and the act of treating).I frequently communicated research progress reports to our collaborators using data visualization and statistical software (Graphpad Prism, Excel), scripting languages (python, MATLAB) and chart diagramming tools (LucidChart) to create easy to understand tables, graphs, and schematics used in my PowerPoint presentations. I hired, trained, and mentored a total of 12 junior scientists throughout my PhD. Four became contributing authors in my scientific publications and three presented 2 posters and 1 podium talk at conferences under my leadership. I primarily used MATLAB with the image analysis toolbox throughout my research.