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OCaml Operators Cheatsheet

One of the hardest parts of learning OCaml is figuring out what the infix operators do, since they’re just a string of symbols and you can’t find them with a Google search. This is my attempt to make a cheatsheet for whenever you’re wondering what a random series of symbols means. Doing a search on this page should find basic info about any of the common OCaml operators.

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Responsible Data Science

As someone who came into the tech industry from the public health field, I feel like I naturally seek purpose and social impact in my work. What does this mean to me as a data scientist? It means that I want to apply machine learning (ML) to real-world problems in a way that prevents, and ideally reverses, the widening social disparities that exist today. It’s this personal mission that drew me to Arena.

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Painless Model Deployment Using PFA

Like most companies in predictive analytics, Arena has two groups of experts with differing desires and skill sets: our data scientists constantly design, test, and refine our algorithms that make predictions to improve health care operations our engineers build efficient, scalable infrastructure to productionalize these algorithms, allowing us to score new input data in real-time. Because of these different goals, there is often a disconnect between model training and scoring. In the past, when it came time to move a new algorithm to production, engineers had to manually reimplement it in another system. Reimplementing anything in software is painful – it comes with more bugs, more iteration, new library requirements, and (because multiple teams are involved) more communication. Any tweaks from the data science team would require additional work by engineering. This situation was becoming a hindrance to our productivity, and we knew there had to be a better way.

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Arena's Cultural Values at Work

At Arena, defining our culture is as important as the quality of the software we deliver. One emanates from the other. In this blog post I share some of our cultural values, using stories of real-life situations to illustrate how we interact with each other on a daily basis: how we go about decision-making, how we prioritize our work, and what we do when things slip through the cracks.

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Cuban Conference Crisis

A year ago I could never have imagined my last night in Havana. I found myself at the hip Fábrica de Arte Cubano, sitting with a glass of Ron Santiago on the rocks, listening to Bartosz Milewski explain how to achieve determinism in a concurrent system using a data structure called lattice variables (or LVars). Previously, I was unhappily programming in Java doing Android Development for a large tech company. After leaving, I found my current position with a small company, Arena, that decided to write most of their software in OCaml. At my company I was introduced [1] to functional programming concepts and the local FP community here in New York City. When my co-worker, Rudi, discovered that there would be an FP conference, Monad Libre, in Cuba, a country still off limits to American tourists, I knew I had to go.

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Go risky on libraries, conservative on infrastructure

This post was a collaboration between Michelle Micallef and Trevor Smith. Trevor is the VP of engineering at Arena. Michelle is an engineer at Arena

Getting a company off the ground is an exercise in risk management. When I was hired to build out engineering here at Arena, I was tasked to form an engineering team and choose our founding technologies. These decisions had to be made to maximize stability, while allowing us to innovate quickly. An important choice was what language our engineers would use. There are many ways a software engineer’s day is impacted by the language [1]. I approached these decisions with a risk management mindset. The idea is simple and commonplace: you weigh the risks of a choice compared with the gain to those involved. This pragmatic strategy was reinforced by a friend who advised me during this time to “go risky on libraries, conservative on infrastructure.” This is what we did.

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