Machine Learning & Distributed Ledger Sr. Engineer
• Responsible for delivery in the areas of: data science/machine learning & Distributed Ledger including technology implementations and algorithm development
• Write software (in Python/R/Java) to extract, clean and manipulate large datasets both structured and unstructured
• Construct data staging layers and fast real-time systems to feed machine learning algorithms
• Review and independently test the effectiveness and accuracy of Image Analytics, NLP and machine learning models
• Utilize expertise in models that leverage the newest data sources, technologies, and tools, such as machine learning, Python, Hadoop, AWS, as well as other cutting-edge tools and applications for Machine Learning.
• Investigate the impact of new technologies, applications, and data sources on the future of secondary mortgage business
• Demonstrated ability to quickly learn new tools and paradigms to deploy cutting edge solutions.
• Develop both deployment architecture and scripts for automated system deployment in AWS
• Create large scale deployments using newly researched methodologies
• Work in Agile environment
• Experience mentoring junior engineers.
• Bachelor’s degree in Mathematics, Statistics, Computer Science
• Comprehensive knowledge of modern statistical learning methods
• At least 5 years’ experience with machine learning and natural language processing
• At least 5 years’ experience with Distributed Ledger technologies
• 5+ years of experience working with AWS
• At least 5 years’ experience in Python (NumPy, SciPy, scikit-learn, pandas, Theras, Theano) and any other open source programming languages for large scale data analysis
• At least 7+ years’ experience in Java
• Master’s Degree in Computer Science
• 2+ years of experience working with financial data
• 5+ years of experience in Python (including NLP) for large scale data analysis
• 7+ years of experience with SQL & relational databases
• Strong communication skills, with the ability to work both independently and in project teams