Slice Labs

Junior Data Scientist

Slice Labs
Apr 2021 – Jan 2023

I joined Slice Labs as a Junior Data Scientist and worked on production machine learning systems in an insurance technology environment, where models directly influenced customer experience and business outcomes.

This role was my first exposure to end-to-end machine learning in the real world. I worked on building predictive models using techniques like logistic regression and decision trees, with a strong emphasis on feature engineering and validation. Improving model performance was important, but understanding why a model behaved a certain way was just as critical.

Beyond modeling, I spent a significant amount of time on data pipelines. I helped automate ETL workflows to reduce data processing time and make reporting more reliable. This work improved how quickly teams could access insights and allowed models to be updated with fresher data.

I also built dashboards and analytical tools that surfaced key metrics for non-technical stakeholders. Communicating results clearly became a core part of the job, not an afterthought. A good model was only useful if people understood what it was telling them.

By deploying models to cloud infrastructure for live scoring, I learned what it means to own a model past deployment. Monitoring, reliability, and integration mattered just as much as training accuracy. This experience shaped how I approach machine learning as engineering, not experimentation.