Engage with business teams to find opportunities, understand requirements, and translate those requirements into technical solutions
Design data science approach, applying tried-and-true techniques or developing custom algorithms as needed by the business problem
Collaborate with data engineers and platform architects to implement robust production real-time and batch decisioning solutions
Ensure operational and business metric health by monitoring production decision points
Investigate adversarial trends, identify behavior patterns, and respond with agile logic changes
Communicate results of analyses to business partners and executives
Research new technologies and methods across data science, data engineering, and data visualization to improve the technical capabilities of the team
Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation
Flex your interpersonal skills to translate the complexity of your work into tangible business goals
Bachelor or higher program in Computer Science, Mathematics, Machine Learning, Natural Language Processing, Deep Learning or a related field
2+ years of programming experience in Python, Java, Scala, or C++
Practical experience with and theoretical understanding of algorithms for classification regression, clustering, and anomaly detection
Familiarity with database modeling and data warehousing principles and SQL.
Familiarity with Big Data tools like Spark, Hive etc.
1+ years of experience with NLP toolkits such as NLTK, OpenNLP, Stanford CoreNLP etc.
1+ years of experience with open source machine learning toolkits: tensorflow, keras, theano, CNTK, scikit-learn, pandas, numpy, libsvm
Huge plus with experience in NLP and chatbots
2+ years of hands-on cloud platform experience: AWS or Azure
Strong knowledge in general software design, data structures, and relational database
Strong written and oral communication skills
Strong analytical skills, data driven mindset
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