Machine Learning Engineer

A rapidly-growing company using the power of technology and data to help merchants and businesses deliver the best pricing to their customers is looking for a Machine Learning Engineer. The engineer will be collaborating with a cross-functional team to solve customers' problems in quick iterations. The start-up is led by a proven founder in an industry that is growing exponentially and on a mission to disrupt the e-commerce industry. This is an excellent opportunity for developers to rub shoulders with industry veterans.

Job Responsibilities:

• Collaborate with e-commerce professionals and lead the creation and development of machine learning models to provide merchants with optimal pricing
• Work on identifying and capturing features that are best suited to achieving accurate predictions such as revenue, price, discussion rates, etc.
• Design and validate machine learning models, conduct research into relevant statistical methods
• Perform data analysis, and provide recommendations to put machine learning models into production

Job Requirements:

• Bachelor’s/Master’s degree in Engineering, Computer Science (or equivalent experience)
• At least 3-5+ years of experience working as a machine learning engineer
• Working with Python should be incredibly hands-on and proficient (Pandas, NumPy, Scikit-learn, etc)
• Python plotting experience is a plus (Matplotlib, etc). 
• Be self-motivated and at ease with owning the complete lifecycle from start to finish
• Comprehend business requirements, and then use technology to address those requirements
• Have expertise accumulating data, interpreting data, constructing and validating predictive models
• Sound ability to deploy completed models with concept-drift monitoring and retraining to generate business benefits
• Real-world experience as a machine learning engineer or data scientist developing and deploying ML models or Deep Learning models
• Proficiency working with at least three of the five key machine learning algorithms: Ridge Regression and Lasso, random forests, linear optimization models, sensitivity analysis, and boosting models
• Proven experience transitioning machine learning algorithms from R&D to product, particularly leveraging Amazon Web Services (AWS)
• Strong analytic abilities
• Experience with dashboards, SQL, and data wrangling is a bonus