Mid-level full stack data scientist: Design, implement and optimize algorithms for unsupervised and supervised learning based on structured and unstructured data. Develop valuable and impactful business insights from social, marketing, industrial data and public policy using advanced machine learning techniques. Apply good coding and model documentation practices. Work closely with the software engineering team to productize analytic applications. Collaborate with system integration and data warehouse engineers on data extraction and data cleaning. Work in a highly interactive, team-oriented environment. - Project Details: Customer analytics, pricing, demand forecast, and risk models. Results will drive business decisions and significant revenue.- Some maintenance work but mostly new development work. MUST HAVES: Statistical and analytical sense, ability to communicate effectively, either R or Python, statistical models, model inference/ interpretation, data visualizations, and machine learning algorithm and package. Creativity and initiative, critical thinking and business acumen.- Good to have: R-shiny, Dash, SQL, GCP, AWS, and operation research.- Alternative Skills they would consider: Related fields where data science techniques are used, including agriculture, economics/econometrics, computer science, biology, math, and physics.- Requires a bachelor’s degree in a STEM or related field and 4 years of experience, or a Master’s degree in same with 2 years, or a PhD.
