Freddy Englender

My main role involves end-to-end ingestion of new data sources and the development of complex data marts and dashboards. I independently led the creation of a dynamic data pipeline for pricing, and later created a Python-based customer attribution model that surpassed prior contractor attempts. I've strengthened my data engineering skills—debugging pipelines, creating terraform infrastructure and resolving upstream issues independently. I was commended for strong communication and leadership in our AI hackathon.

At Florence I had the opportunity to lead a data function through both the challenging post-covid market as well as a successful series B funding round. I designed analytics pipelines from top to bottom as well as our delivery strategy.

I was particularly proud of our strides in increasing the reliability of our data infrastructure, mainly through the use of testing and documentation.

It was very enjoyable helping Florence to maintain and increase data adoption through the growing pains of a startup like internationalisation and major product changes. Projects: automated document reviews, client negotiation tools, retention analysis + more

Here we implemented fraud and money laundering prevention models, primarily through the use of Databricks and Looker. My role was to contribute towards the creation and testing of factors as well as aid collaboration with operational and commercial functions. I was also able to use my extensive Looker experience to help with defining best practice and onboarding new users.