Join a high-performing, tight-knit team at a fast-growing company that is using the Internet of Things (IOT) to transform how organizations sense, monitor, and make decisions. Founded out of MIT in 2005, Smart Sense is trusted by more than 2,000 organizations, including Walmart, SpaceX, Apple, CVS Health, Coca-Cola, and the US State Department to help them make sensor-driven decisions. We have a solution that our customers rely on every day to make mission critical decisions; we are looking for team-oriented change agents to help shape the future of IOT.
What We Offer
In this Data Scientist Machine Learning Engineer role, you will be a key contributor on our path towards prescriptive analytics. Our data science machine learning efforts will plumb the entire breadth of our data topology from raw data ingestions to cold storage while you buildout machine learning capabilities. This is an exciting opportunity for a Data Scientist Machine Learning engineer ready to make a discernable impact on our business by advancing data maturity at SmartSense creating data products that delight our customers. Join us on our data journey today.
Who You Are and What You Bring
- Work closely with product owners, software leadership, UX, and data team to translate business requirements into technology design and solution
- Convert data science outputs into best practice, production-grade software
- Enable effective decision making by retrieving and aggregating data from multiple sources and compiling it into a digestible and actionable format
- Develop expertise in a broad range of data resources and know when, how, and which to use and which not to use
- Drive innovations and efficiency by implementing new business process through technology solutions and the definition of new data models
- Perform data exploration, data visualization, and data analytics to better understand multidimensional first party and third-party data
- Participate in sprint planning and other project activities required by Agile software development methodology
- Develop as-is and to-be process flows, data flow diagrams, reporting and data requirements and data mapping documents
- Design, implement, test, deploy, and scale production ML
- Work closely with Data Engineering to develop data pipeline needed for ML
- Work closely with other data operations to integrate ML with other services on AWS
- Implement, scale, and maintain machine learning pipelines to provide value to our customers.
- Monitor production models and collaborate with data engineering on systems to ensure quality and protect against data drift
Desired But Not Required
- Experience with Kubernetes deployments
- Experience with deploying machine learning models in GCP and AWS
- Experience with MongoDB
- Experience with Red Panda or Mage
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