Data Scientist - Data Scientist

•Masters degree required in Statistics, Operations Research, Mathematics, Economics, Computer Science, Engineering, Physics, Chemical Engineering or field of comparable foundations in mathematical and statistical analysis through the use of models, algorithms or programmed solutions.
• 5+ years experience with any of the following programming languages: R, Python, Java, C++, C#, Scala, SAS, MATLAB or similar scripting languages. Similar experience and proficiency with SQL are required.
• 5+ years experience across a breadth of data science, AI and machine learning disciplines including, but not limited to: forecasting, natural language processing (topic modeling, semantic search, text classification), deep learning and GPU-based algorithms (CNN, LSTM), computer vision
• 5+ years designing experiments and researching novel solutions beyond established literature or documentation
• Experience with data mining processes (SEMMA, CRISP-DM), data preparation, consolidation, imputation, transformation, interaction, variable reduction, modeling, maintenance, and post-mortem analysis.
• Experience with statistical methods such t-test of means, Tukey-HSD tests of means on groups, ANOVA, Proportion tests, data normalization and scaling, univariate and multivariate outlier detection.
• Experience with modeling techniques such as linear models, decision trees, neural networks, k-nearest-neighbor, support vector machines, cluster analyses, and ensembling methods.
• Strong Oral and Written skills.
• Experience with Agile Software Development.
• Experience in a large corporation or consulting firm with focus in marketing strategies, modeling, CRM and management sciences/statistics highly desired.
• Experience with Deep Learning tools and packages such as TensorFlow and Pytorch.
• Experience with frameworks and languages designed for big-data analysis, including Hadoop, Spark, Hive, and Pig.
• Experience with cloud computing frameworks or APIs such as Microsoft Azure, Amazon Web Services and Google Cloud Platform.
• Experience with developing, releasing, and maintaining machine-learning projects across the entire-ML lifecycle through sandboxed environments, logging, unit-testing, and including other software engineering best-practices.
• Must have published articles in a peer-reviewed scientific or academic journal, or filed patents in the fields of data science, artificial intelligence or machine learning.
•Ph.D. degree in a quantitative field preferred, but will also consider candidates that are currently enrolled in a Ph.D. program.