The Machine Learning Engineer will develop predictive models using various ML algorithms and mining techniques to help our customers experience success using Splice Machine, making better decisions faster.
You take pride in working to understand, quantify and verify the business needs of customers and their specific use cases, translating these needs into models using Splice Machine that help them make decisions.
You have a strong understanding of ML and statistical models and methods (time-series analysis, regression, hypothesis testing) and experience with large scale solutions in Spark, H20, TensorFlow or comparable ML architecture.
You are comfortable asking for the appropriate data from the customer and presenting your analysis, results and recommendations.
You are technical and are accustomed to working with researchers, data scientists and project managers to ensure the best implementation practices and use of the Splice Machine product.
You are results oriented and a high achiever.
About What You’ll Work On
Develop predictive models using various ML algorithms and mining techniques to help our customers make better decisions faster.
Deliver on data science activity, working in a cross-functional team of Splice Machine and customer resources.
Build our customer’s trust by maintaining a deep understanding of our product capabilities and their business needs.
Use predictive algorithms and OLAP data processing in Splice Machine to:
Predict oil rig outages from IoT sensor data Predict code blue events from hospital electronic medical records
Predict late supply chain orders from ERP and radio-frequency tag data
Predict the best drug to give to a patient given lab results and patient reported outcomes
Predict fraud from claim data Predict loyalty offers from supermarket POS data