Machine Learning Engineer
RESPONSIBILITIES:
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Design and develop scalable ML/AI solutions to solve diverse business challenges by deriving features from rich data sources, training, evaluating and deploying models to production using cutting edge technologies
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Gather and analyze data to perform statistical analysis, identify key factors and build comprehensive visualizations to report findings
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Utilize statistical methods to process, clean and validate data for uniformity and accuracy
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Create and maintain end-to-end data pipelines and APIs according to business requirements
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Communicate analytic solutions to stakeholders and implement improvements as needed to operational systems
QUALIFICATIONS:
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Experience using statistical computer languages, such as R or Python (preferred)
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Experience working with large data sets (> 1TB) and using big data solutions such as Hadoop, Hive, Spark, Storm, MongoDB etc.
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Experience specifically with deep learning (e.g., CNN, RNN, LSTM) and NLP frameworks
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Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, etc. and their real-world advantages/drawbacks
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Rigorous understanding of statistics and ability to discern appropriate statistical techniques to problem-solve
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Proficiency with writing SQL queries
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Experience with data visualization tools, such as Tableau, is a plus
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Prior work experience in the financial industry is a plus