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- A minimum of 5 years of developing and running models in non-academic production systems. Please note that applications without this experience will not be considered. Some of this experience needs to with NLP and deep learning technologies.
- Masters or Ph.D. with experience in Machine Learning/Statistics/Data Science
- Experience with traditional as well as modern machine learning/statistical techniques, including Regression, Classification, Regularization, NLP, NLU, Ensemble Methods and Neural Networks
- Strong implementation experience with high-level languages, such as Python, R, Perl, Ruby, Scala or similar scripting languages.
- Familiarity with Linux/Unix/Shell environments.
- Strong hands-on skills in sourcing, cleaning, manipulating and analyzing large volumes of data.
- Strong written and oral communication skills.
- Intense intellectual curiosity – strong desire to always be learning
- Analytical, creative, and innovative approach to solving open-ended problems
- Highly collaborative, team-player attitude
- Experience with product development is a plus
- Experience with Financial Services is desired but not required. Much of our data relates to Investment Banking and M&A.
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