philrenaud

I've been building a Chrome extension[0] that highlights and shades data tables on the web.

It's a fun little problem because you'd think there's an easy rule to apply, like "big numbers = green, small numbers = red, scale accordingly" but 1. a ton of data is just the opposite (like Earthquake casualties, or Batter strikeouts) or even ambiguous (like "cost" as a column header)

So I've been using Jev (and other small decision models) to make decisions about cardinality and ordinality of the data before I shade it. It's become a super fun problem to solve as a result.

[0]: https://practicaldata.dev/. It's open source.

Hi! I work with ad-hoc datasets a lot and Chrome is my main lens into them. I decided to build an extension that shades the comparable columns of those tables the way a spreadsheet's conditional formatting would.

Quickly figured out that there's a problem with just applying "big numbers = green, small numbers = red" uniformly, though. On my fantasy football team page, "number of fumbles" should show green when a player has few / red when they have many.

When TypesafeAI's Jev decision model was released, it seemed like a really good fit for being able to solve this sort of problem. With some context (like "does `cost` here seem like a good thing or a bad thing, given the title of the table and adjacent columns), it is great (and quick!) at determining expected order.

Was already doing the work of parsing numbers from cells, so things like "$50-60k" becomes comparable and so do cells with adjacent text (like "32.4% Xhigh effort").

It's all open source[0] and you can BYOK (for Jev or Clef) or use it for free (with some healthy limits)

I hope you like it!

[0]: https://github.com/philrenaud/practical-data

Serendipitous timing, but I've been building a little chrome extension [0] for doing exactly this sort of thing (highlighting tables automatically, especially when numbers don't necessarily correlate good=green, bad=red). Model pricing and comparisons are one of the main things I checked (low cost good, high benchmark score good).

[0] Practical Data (https://practicaldata.dev/ / https://chromewebstore.google.com/detail/practical-data/oeoo...)

Nylas | New York, San Francisco, Toronto, or Denver | U.S./Canada, Remote-OK | https://www.nylas.com

Our mission is to empower the world to communicate with context and insight. The Nylas Cloud APIs powers email, calendar, and contacts features in SaaS products ranging from CRM and marketing automation to recruiting tools, scheduling assistants, legal and real estate platforms, and more. The Nylas email API integrates with 100% of email service providers, allowing bidirectional email sync between SaaS apps and your email client.

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Affinio | Toronto, Ontario or Halifax, Nova Scotia, Canada | Full-Time | http://www.affinio.com/careers/

Affinio is building a data platform that lets users run unsupervised machine learning against large datasets, like social networks and permutations thereof. We're looking for data-minded back-end engineers, architects, and QA devs.

Scala (Play, Sangria) with a graphQL API layer. Data dashboard is in Ember. Lots of D3, lots of statistics, lots of type safety.

We're funded and have about 20 open positions today: http://www.affinio.com/careers/

Reach out to me at https://twitter.com/phil_renaud if you've got questions!

Affinio | Data-focused Software Engineers and Architects, Project Mangers, QA Engineers | Full-time/Onsite | Toronto, Ontario / Halifax, Nova Scotia

Affinio is a well-funded Data Science startup that helps users make predictions and gain insights about really complicated graphs, such as social networks like Twitter and Reddit. We have a stack that spans from Spark to Scala to Ember, expose a GraphQL API, and write a lot of serverless-style code.

To see all open positions visit http://www.affinio.com/careers/

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Come help us build tools to let users get a really, really deep understanding of social networks and their connections. Our backend is written in Scala (Play) and we've recently converted our API to GraphQL (which has been a dream to work with tbqh).

Even if you're new to Scala but your Java is up to speed, we definitely want to talk to you.

Check out the job listing here: http://www.affinio.com/careers/backend-developer-platform

Affinio | Back-end Engineer | Halifax or Toronto | http://affinio.com

Affinio is a marketing intelligence platform that leverages social graphs to understand consumers. We help agencies, media companies, publishers and brands come up with and evaluate their creative marketing strategies.

Our stack is Scala (Play) and Javascript (Ember.js) with a healthy amount of Java, Python and PHP. We're GraphQL-friendly and generally pretty buzzword compliant.

We're building a new Integrations team and have several positions open -- head over to www.affinio.com/company to apply.

Affinio | Halifax or Toronto, Canada | Full-time | http://affinio.com

Affinio builds data products that revolve around social graphs and the clustering thereof. We're looking for QA testers with experience with JS single-page apps and web-facing API testing. http://www.affinio.com/company/quality-assurance/ to learn more!

Data Scientist and Backend Engineers | Affinio | Halifax, Nova Scotia, Canada | Full-Time | Remote/Onsite

Affinio analyzes complex network graphs to come up with concepts like influence, trends, and density for groups on social networks. If you love working with clustering algorithms and graph data sets, we'd love to talk to you.

Find out more: http://affinio.com/engineering

Real-life fallout 3?