Experienced Data Scientist in San Jose, California

DUTIES: Design and develop Predictive Analytics and Prescriptive Analytics architecture and features for artificial intelligence software solutions, including developing machine learning and statistical models to perform big data analysis. Duties will include the following: Research, design and develop algorithms and techniques to perform data manipulation and transformation; build generative and discriminative models to perform clustering, classification, regression, and recommendation systems; design and build custom machine learning models; build and implement machine learning algorithms to plan, create, coordinate, and deploy business information solutions; gather business requirements and technical specifications for developing analytics solutions; develop artificial intelligence and machine learning algorithms; custom design and implement various techniques in machine learning such as support vector machines, neural networks, genetic algorithms, principal component analysis, cluster analysis, k-means, decision trees, random forests, regression analysis, Bayesian analysis, Naïve Bayes, and deep learning; analyze large, complex, multi-dimensional data sets; develop analytic solutions using R, Python, Scikit-learn, SQL and similar statistical tools and frameworks; and utilize Deep Learning neural networks including RNN, CNN, LSTM, and Autoencoder to predict the behavior and performance of businesses.

REQUIREMENTS: Master’s degree (or equivalent*) in Data Informatics, Computer Science, Applied Mathematics, Statistics, Analytics or a related field such as Computer Science and Engineering and two (2) years of relevant experience in the job offered or as a Software Engineer, Software Engineering Analyst, Application Developer, Programmer Analyst, or Data Science Intern, including two (2) years of experience with algorithm design and development; software architecture development; data engineering, data structures, and data visualization; statistical data analysis; Artificial Intelligence (AI) and deep learning techniques; feature synthesis, engineering, and hyper-parameter tuning; Natural Langaage Processing; Machine Learning, including Bayesian modeling, multivariate and logistic regression, support vector machines, cluster analysis, decision and regression trees, random forest, neural networks and ensemble methods; analyzing large, complex, multi-dimensional data sets and developing analytic solutions; experience in predictive analytics using R, Python, Scikit-learn, and SQL, PostgreSQL statistical tools; and Spark, Hadoop, Unix O/S, Github; and programming languages C/C++, Java, Python, R.

*As determined by properly evaluated credentials. Scry Analytics, Inc. will accept any other suitable combination of education, training or experience.