Job Description :
Qualifications Required
Minimum of 5+ years Machine learning/Data experience. A Master’s degree.
Strong with Statistics and mastery of statistical programming languages such as MATLAB (must), Python, R.
Working knowledge of Hadoop, Apache Spark, and other big data technologies.
Experience and passion for simulations, optimization, neural networks, artificial intelligence (deep learning and machine learning)
Mastery of various statistical methodologies such as regression analysis (linear and non-linear), cluster analysis, CHAID, time series, survival models.
Knowledge of statistical theories and techniques commonly used in recommendation, prediction, anomaly detection and optimization models.
Ability and desire to go beneath the surface of a problem and distill it into a clear set of hypotheses that can be tested.
Ability to identify, join, explore and examine data from multiple disparate sources and formats
Ability to reduce large quantities of unstructured or formless data and get it into a form in which it can be analyzed
Strong analytic thought process and ability to interpret findings.
Experience in data wrangling and advanced analytic modeling.
Strong communication and organizational skills and has the ability to deal with ambiguity while juggling multiple priorities and projects at the same time.
Knowledge and experience using one or more of the following, or similar, machine learning software frameworks: CAFFE, Torch 7, Keras and Tensorflow
Experience building production-ready NLP or information retrieval systems.
Experience with Logistics data.
A masters degree in CS.
Hands-on experience with NLP tools, libraries and corpora (e.g. NLTK, Stanford CoreNLP, Wikipedia corpus, etc