I'm a seasoned data scientist always looking for my next challenge, a lifelong-learner, intensely curious about the world, and driven to make a difference.

I currently work at ID Analytics, a consumer risk solutions company in San Diego that builds machine learning models to prevent identity fraud and help companies make smarter lending decisions. My approach to data science is to start big and broad, deeply understand the problem context, define my KPI's, create a roadmap and then apply laser focus to solving one step at a time. This framework has helped me tackle a wide array of data science problems, from hands-on work like data pipeline automation to more experimental projects involving algorithm development.

Like most data scientists, my path here was a long and winding road of self-teaching, on-the-job experience, and structured education, driven by a desire to use data to scientifically solve tough problems. My first post-college job in a marketing analytics startup opened up my eyes to the power of data, and inspired learn everything I could about coding and modeling. I moved onto working as a data science consultant at a communications agency in Paris, where I helped them use social media data to measure and analyze online conversations. To better orient myself in the universe of data science I attended Galvanize's Immersive Data Science program in San Francisco, where I pushed myself to soak up a firehouse of knowledge from practiced professionals. I stayed on as a Data Scientist in Residence at Galvanize, helping teach students a wide range of data science subjects ranging from statistics to NLP to unsupervised learning. I've been at ID Analytics since 2017, working on projects ranging from model building to data evaluations to experimentation in applying the latest algorithms to our data.

I always love talking to fellow and aspiring data scientists, so please reach out and start a conversation with me if you want to talk data!