This position will help with Analytics in particular asset utilization including hours, location, and other telemetry data.
The candidate will work on a variety of tasks including data pipeline, documentation, and model development so the team can continue to lead in the space of asset utilization.
This effort might also involve work on forecasting, so understanding forecasting techniques is a plus.
A typical day for this position includes a mix of meetings and individual contributions, with occasional travel (if approved) to participate in in-person workshops.
The candidate is expected to participate in twice-a-week stand-ups, product, and release reviews, and with individual team members to build knowledge.
The position will be an onsite hybrid in Chicago, in the office about once a week.
Job Description:
Experience applying python libraries Pandas, NumPy, Matplotlib, Scikit-learn, Keras, and TensorFlow to solve business challenges.
Experience with Snowflake and SQL.
Experience with advanced data analysis and statistical methods such as regression, hypothesis testing, ANOVA, statistical process control, etc.
Familiarity with Agile (scrum, tickets, sprint, reviews).
Must be competent with analytics, forecasting techniques, and tools.
Must be comfortable working in industry-standard statistics, analytics, and data visualization packages.
Practical applications of machine learning techniques such as Clustering, Logistic Regression, Random Forests, SVM, K-Means, PCA, XGboost, and Neural Networks.
Azure DevOps
Experience with cloud technologies, AWS.
Soft Skills
Must demonstrate strong initiative, interpersonal skills, and the ability to communicate effectively.
Good communication Good presentation skills Good collaboration
Education Requirements:
Bachelor's degree, preferably in engineering, computer science, statistics, economics, or mathematics.