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Startups Using NumPy in Boston

Via their job posts and information submitted by startups themselves, these are the Boston NumPy startups we've found.

Interested in other technologies? Browse or search all of the built-in-boston tech stacks we've curated.

Automatic engineering team report generation, for better management visibility into team performance & strategic alignment.

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AI-powered tech for evaluating photos of a vehicle, detecting damage, and automating claim estimation.

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Using computer vision & machine learning to turn human or animal body language into structured data, helping to develop better drugs for diseases like ALS, Parkinson’s, and Alzheimer’s.

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High-accuracy weather tools by integrating existing weather data with analysis of the impact on cellular signals.

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Software for electric grid congestion and routing management.

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iPad docks & point-of-sales software for retailers.

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Interpreting and visualizing real-time patient data in the ICU for better critical care decision making.

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Employee performance prediction tools for hirers / recruiters.

Tech Stack Highlights

MySQL – MySQL is used to provide the main data storage for all business critical information such as user data, jobs, candidates, assessments meta-data etc. We use NDB cluster as well as full redundancy real-time back-up server. Additionally the data is archived hourly, daily and weekly. When it comes to data security – nothing is ever too much.

MongoDB – Thousands of data points a minute are streaming to our servers in the form of user responses to pre-employment assessment answers. This data constitutes the main material for later analytics. Mongo’s Sharding technique allows us to employ multiple low cost instances to handle all this data in parallel fashion. Like MySQL data, No-SQL data is fully redundant and backed up on regular basis.

Python/R – Both Python and R are used to automate the data analytics, required for creating job-success predictions. While Python provides a much more versatile and reliable development environment (especially with modules like NumPy, Pandas, etc), R still has advantages in certain areas. Python’s rpy2 module make the two work together pretty decently.

Apache/PHP – Since our web application is a single-page app, the web service is mainly used as a REST-style backend that interacts with the browser by sending back-and-forth JSON packages. Memcached allows to maintain single state between all web instances. Other great tools like WKPDF (that is used for server-side web rendering) for creating downloadable materials, etc.

JavaScript/Web MVP – On the client we took a rather unorthodox approach of creating our own MVP framework that connects seamlessly with the backend, and makes the entire development cycle much faster. The framework that we created (ElementsJS) makes use of jQuery as well as multiple open-source jQuery plug-ins, while binding them together in a simple to use JavaScript API.

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