The CognitOps Story
CognitOps is a cloud and ML-driven supply chain startup founded in 2018 and headquartered in Austin, TX. Our purpose is to improve supply chains through better operations management. We're building the brain for every warehouse in the world (and eventually on Mars) to help leaders make faster and better decisions, and we hope you can join us!
CognitOps was founded by a team of lifelong supply chain technology builders. We realized that today's supply chains are unsustainable and wasteful for businesses, jobs, and the environment. And with the support of our family, friends, pets, and investors, we chose to take this challenge head-on bravely. Backed by some of the best VCs in the industry, we began our pursuit of unleashing ingenuity to give rise to resilient businesses.
We tackle cool, challenging problems. For example, we help warehouses supply hospitals with PPE and critical medical equipment more efficiently. We help e-commerce businesses ship orders on time. We tackle these challenging problems using modern technologies like machine learning, queue-based simulation, Google Cloud, Kubernetes, Kafka, and Scala. Our team has decades of startup experience working with big data and building scalable, fault-tolerant, secure software and decades of experience working with warehouses and empathetically understanding the needs they have. We're still a small early-stage company. So you'll have an opportunity to come in, make a huge impact, and be a leader as the company grows. But at the same time, we have significant early customer traction and are already on an accelerated growth path. We believe in having a fun, loose work environment while also fostering a culture grounded in grit, accountability, innovation, collaboration, and bravery.
Supply chains are struggling to evolve. For every 1 billion dollars of e-commerce growth, North America builds 1 million more square feet of warehousing. Yet, warehouses are fraught with waste. Why? Because operations managers and leaders have never had the tools to manage their facilities correctly. It’s mind-boggling to think that the industry continues to invest in robots and point solutions that only perpetuate this broken model. This challenge is compounded by people understandably not wanting to work in these environments. We can fix this together. We can build in the cloud, apply machine learning, build unique products and datasets, and be nonconformists always challenging the status quo together.
What You Bring
Experience in successfully…
- Using data, mathematics, machine learning, statistics, and coding to solve real-word business problems that create real value for stakeholders;
- Collaborating with technical and non-technical professionals to define and deliver high-quality solutions, quickly;
- Bring analytics and machine learning models to production;
- Writing clean, maintainable code and doing truly reproducible research;
- Developing deep empathy for users and customers;
- Excellent capacity to communicate about complex technical issues with broad and diverse audiences --- both technical and not; and,
- Constantly learning new approaches, methods and tools. You show the exuberant curiosity of a lifelong student.
The following creds get us interested…
- A demonstrated history of delivering solutions and prioritizing getting things done over getting things perfect
- Expertise with the standard Python scientific stack: numpy, scipy, pandas, scikit-learn
- Knowledge of modeling best practices
- You don’t think a data scientist’s job stops when the model converges -- you want to see project through to the end and aren’t satisfied until users see real value
- You know when linear regression is the right choice, and when to reach for something more complicated
The following creds get us excited…
- Experience with observational causal modeling, deploying deep learning models, online model training, or user-facing model interpretability
- An ability to contribute to ETL pipelines at scale; we use Spark, Scala, Kafka and other modern tools to move our data around
- Knowledge of MLOps practices and technologies for deploying machine learning in a SaaS environment; we use MlFlow, Airflow, Docker and other tools to manage a continuous training and delivery pipeline for our models
- You care about what you do
- You care about what we do
- You live our values
We want to see your problem-solving and analytical skills. Be prepared to write good, clean code. You don’t need to know our entire stack, but we’re looking for practical experience. We want to see that you can deliver practical solutions to meaningful research problems. Our hiring process is swift:
- Recruiter Phone Screen
- Hiring Manager Screening
- Team Interview
- Values Interview w/Co-Founders
Life at CognitOps
At CognitOps, being an Equal Opportunity Employer means more than upholding discrimination-free hiring practices. It means that we cultivate an environment where people can be their most authentic selves and find both belonging and support. We're on a mission to change supply chains -- an experience made whole by our unique backgrounds and perspectives.
We encourage our employees to care for their whole selves with reimbursed and hassle-free health benefits through our HRA, truly unlimited paid time off, paid parental leave, safe company social events, and freedom to pursue volunteer opportunities.