Machine Learning Engineer

• 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

• Gather and analyze data to perform statistical analysis, identify key factors and build comprehensive visualizations to report findings

• Utilize statistical methods to process, clean and validate data for uniformity and accuracy

• Create and maintain end-to-end data pipelines and APIs according to business requirements

• Communicate analytic solutions to stakeholders and implement improvements as needed to operational systems

• Experience using statistical computer languages, such as R or Python (preferred)

• Experience working with large data sets (> 1TB) and using big data solutions such as Hadoop, Hive, Spark, Storm, MongoDB etc.

• Experience specifically with deep learning (e.g., CNN, RNN, LSTM) and NLP frameworks

• Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, etc. and their real-world advantages/drawbacks

• Rigorous understanding of statistics and ability to discern appropriate statistical techniques to problem-solve

• Proficiency with writing SQL queries

• Experience with data visualization tools, such as Tableau, is a plus

• Prior work experience in the financial industry is a plus