Recent submissions

Comment · 2 years ago
Comment · 5 years ago
Counterpoint to that is when a recruiter initiates contact they are often very coy until they have you on the phone, frequently not even sending a JD until after that first conversation (where this line of questioning usually arises). I get wanting to provide an engaging response but hard to do so until the recruiter has provided sufficient information.
Comment · 5 years ago
Certilytics | Hiring Data Engineers, Product Managers, Analysts, Developers, and more | Remote: US Only | Full-time

Certilytics provides sophisticated predictive analytics solutions to major healthcare organizations by integrating financial, clinical, and behavioral insights. Our team represents a dynamic infusion of multidiscipline, which includes actuarial, data, and behavioral scientists, IT engineers, software developers, nurse clinicians, and experts in public health and the health insurance industry. Certilytics has extensive experience working with a diverse set of customers, including large self-insured employers, health plans, pharmacy benefit managers, government programs, care management companies, and health systems. These relationships with various data providers and customers allow for rapid data ingestion, validation, and enrichment, as well as streamlined delivery of analytic dashboards, outputs, and visualizations to our customers. Our unique approach allows for developing the most accurate financial, clinical and behavioral models in the industry.

Why Certilytics! Access to one of the most extensive clinical datasets in the industry that includes medical claims, pharmacy claims, and laboratory data. Impactful work. We're big enough to have the freedom to take on interesting projects but small enough that your work is always important and highly visible within the organization. Remote friendly. The Certilytics team is distributed throughout the US and has regular in-person working sessions for all of those little things that are hard to accomplish over Teams.

See our open jobs: https://jobs.silkroad.com/CarewiseHealth/Certilytics

Comment · 5 years ago
Certilytics | Hiring Data Scientists and Data Engineers | Remote: US Only | Full-time

Certilytics provides sophisticated predictive analytics solutions to major healthcare organizations by integrating financial, clinical, and behavioral insights. Our team represents a dynamic infusion of multidiscipline, which includes actuarial, data, and behavioral scientists, IT engineers, software developers, nurse clinicians, and experts in public health and the health insurance industry. Certilytics has extensive experience working with a diverse set of customers, including large self-insured employers, health plans, pharmacy benefit managers, government programs, care management companies, and health systems. These relationships with various data providers and customers allow for rapid data ingestion, validation, and enrichment, as well as streamlined delivery of analytic dashboards, outputs, and visualizations to our customers. Our unique approach allows for developing the most accurate financial, clinical and behavioral models in the industry.

Why Certilytics!

Access to one of the most extensive clinical datasets in the industry that includes medical claims, pharmacy claims, and laboratory data.

Impactful work. We're big enough to have the freedom to take on interesting projects but small enough that your work is always important and highly visible within the organization.

Remote friendly. The Certilytics data science team is distributed throughout the US and has regular in-person working sessions for all of those little things that are hard to accomplish over Teams.

Tech Stack: Python, TensorFlow, Kubernetes, AWS, Spark, Scala

See our open jobs: https://www.certilytics.com/contact-us/#careers

Comment · 6 years ago
Comment · 7 years ago
Does this do experiment tracking similar to MLflow? I’m trying to figure where these two overlap and where they diverge.
Comment · 8 years ago
A subscription to safaribooksonline.com ($399/year) is my favorite way to spend part of my learning budget. Having access to the entire catalog of O’Reilly (and it’s affiliates) books is awesome. Access to conference recordings from Strata is really nice too.
Comment · 8 years ago
Basically just the ability to run on Linux.
Comment · 8 years ago
Any chance of this being offered for on-prem install in the future? Looks interesting but cloud only makes it a no go for my team.
Comment · 8 years ago
From my experiences (currently work with several Fortune 100 health insurers/benefits managers, and have previously worked for another large insurer, a major academic medical center, and a large pharma company), healthcare organizations tend to be rather cloud adverse (most of our contracts very explicitly forbid us from using any form of 3rd party cloud computing). So while I agree that much of the heavy lifting will shift to the cloud (or already has), I expect health analytics will continue to favor on-premises solutions (GPU’s still tend to be pretty rare compared to CPU based clusters but are slowly becoming more common).
Comment · 8 years ago
That's fair. Google's recent paper on predicting patient deaths is another good example of this (logistic regression + good feature engineering performed just as well as their deep learning models, and the logistic regression has the added benefit of being significantly more interpretable and as a result, actionable).

It'll be interesting to see when specialized ML focused silicon will become readily available. Right now I find ML libraries that are able to run on blended architectures (any combination of CPU and GPU's) much more exciting/impactful than TPU's. The ability to deploy on just about any cluster a customer may have available is huge.

Comment · 8 years ago
Comment · 8 years ago
Being rules based isn't necessarily a bad thing or disingenuous. I develop healthcare AI products (ML/DL researcher) and we actually aim to be able to translate our models into a rules based engine (find a strong signal, interpret/understand model well enough to translate/embed into a rules engine, look for a new signal in our models, rinse + repeat). We end up deploying a mix of rules based and true ML based models into production but it may not be immediately obvious to the end user which type of model they are using.
Comment · 8 years ago
Healthcare data can't be shared the way the browser histories, cell phone location data, etc. can. It's a completely different set of a rules that people have to play by (HIPPA for example). I build machine learning systems using healthcare claims and EHR data and without the direct cooperation of several large insurance companies (and access to their data) we'd be dead in the water. Even with access to their data there are incredibly strict limits to what we can and can't do with it. You can't just go out and collect healthcare data the way you can many other types of data.

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