Data Engineer

Position Summary

This position will be located within (Dev/IT) and work closely with computer scientists, IT and data scientists to deploy and optimize machine learning models in the Paycom production system environment.

Responsibilities

• Work closely with IT/Computer Scientists on technical aspects of deploying machine learning models in production.
• Work closely with Data Scientists to understand, implement, refine, design, and test deployment of machine learning models in production.
• Optimize the environment for production machine learning models to access and handle data more efficiently and ensure scalability.
• Designs new processes and builds large, complex data sets needed for machine learning processes.
• Serve as SME on machine learning technology and recommend acquisition of appropriate technology for production purposes.
• Advise and assist IT/infrastructure on install and configuration of machine learning systems.
• Explore, design, and implement a robust production-grade data processing pipeline that can ingest, aggregate, and transform large datasets.
• Independently conduct literature search to keep informed of best practices and new methods.
• Serve as on-call for production issues related to machine learning processes.

Education

• BS degree in Computer Science or related field with 5 years machine learning engineering experience or MS/PhD degree in Computer Science or related field with 3+ years of machine learning engineering experience.

Experience

• 3+ years hands-on experience deploying production-level machine learning algorithms and productionizing them at scale in a distributed computational environment.
• 1+ year experience with R. Working knowledge of R required.
• Experience working with large, messy real-world data.
• Experience with SQL, Ruby, Python, C#, Pig and other query and programming languages.
• Experience with machine learning database tools and platforms such as HBase, Mongo, Hive, Cassandra, MySQL, SQL Server, PostgreSQL, Hadoop, Spark.
• Experience with machine learning optimization tools and related technologies such as H2O, Theano, mlpack, TensorFlow. Experience with H2O required.
• Experience with machine learning platforms for production models such as Apache, Pattern, Shogun.

Skills and Abilities

• Strong expertise in computer science fundamentals: data structures, performance complexities, algorithms, and implications of computer architecture on software performance such as I/O and memory tuning.
• Working knowledge software engineering fundamentals: version control systems such as Git and Github, workflows, ability to write production-ready code.
• Strong knowledge of data architecture and system/pipeline and data processing engines such as Spark and Hadoop.
• Working knowledge of R and Rstudio.
• Working knowledge of SQL, Pig, Python, and other query languages.
• Knowledge of C++, PHP, Java and other languages.
• Knowledgeable with machine learning tools and frameworks like Python, Spark, H2O, Theano, mlpack, TensorFlow.
• Knowledge of machine learning platforms such as Amazon, IBM Watson, Azure, Google Predict, BigML
• Strong trouble-shooting skills.
• Knowledge of technical infrastructure.
• Knowledge of installation and configuration of machine learning systems/technology.
• Strong technical aptitude.
• Basic knowledge of statistics, calculus and probability, experimental design, and machine learning techniques to enable conceptual understanding of Data Scientist’s models.
• Has strong critical thinking skills and the ability to relate them to the products of Paycom.
• Possesses a combination of creative abilities and business knowledge.
• Demonstrates excellent verbal and written communication skills as well as the ability to bridge the gap between data science and business management.
• Displays exceptional organizational skills and is detailed oriented