We are seeking engineers or applied scientists who have expertise in implementing data mining and machine learning systems to contribute to the development of an innovative online education platform that is tailored to the unique needs of each student. Your responsibilities will include: - Demonstrating a strong passion and enthusiasm for constructing scalable systems that can analyze extensive datasets and provide actionable insights. - Showcasing a proven track record of identifying connections within vast and seemingly unrelated datasets. - Displaying the ability to work with incomplete or imperfect data sets effectively. - Possessing knowledge of linear algebra and proficiency in manipulating data through matrix algorithms. - Having the capability to develop and interpret probabilistic models of intricate, multi-dimensional systems. - Demonstrating experience in quantitative analysis using Python. - Having familiarity with database technologies like SQL. - Showcasing solid programming skills in Java, C, C++, or Python. Preferred experience with the following technologies: - Collaborative filtering. - Decision trees and automatic tree generation. - Bayesian methods. - Clustering techniques including principal components analysis, k-means, etc. Desired qualifications include: - Proficiency in Hadoop or other MapReduce implementations. - Experience in semantic text mining or natural language processing. - Prior involvement in high-stakes information retrieval and statistical analysis, such as Bioinformatics or Fraud Detection. If you believe you meet these qualifications and are excited about this opportunity, please send your resume to info@zunopy.com.,
You will be working on building an innovative online education system that adapts to each individual student. Your responsibilities will include: - Passion and enthusiasm for building scalable systems that analyze huge data sets and make actionable recommendations - Proven ability to identify relationships within large, not obviously related data sets - Ability to work with incomplete or imperfect data - Familiarity with linear algebra and manipulating data using matrix algorithms - Ability to build and interpret probabilistic models of complex, high-dimensional systems - Experience with quantitative analysis utilizing Python - Experience with database technologies such as SQL - Solid programming experience utilizing Java, C, C++, or Python Preferred technologies to be used include: - Collaborative filtering - Decision trees (and automatic tree generation) - Bayesian methods - Clustering techniques (principal components analysis, k-means, etc.) Additionally, we would like you to have experience in: - Hadoop or other MapReduce implementation - Semantic text mining or natural language processing - Experience in high-stakes information retrieval and statistical analysis (e.g., Bioinformatics, Fraud Detection) If you are interested in this opportunity, please forward your resume to info@zunopy.com.,