- 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.
- 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
Paycom is an equal opportunity employer and prohibits discrimination and harassment of any kind. Paycom makes employment decisions on the basis of business needs, job requirements, individual qualifications and merit. Paycom wants to have the best available people in every job. Therefore, Paycom does not permit its employees to harass, discriminate or retaliate against other employees or applicants because of race, color, religion, sex, sexual orientation, gender identity, pregnancy, national origin, military and veteran status, age, physical or mental disability, genetic characteristic, reproductive health decisions, family or parental status or any other consideration made unlawful by applicable laws. Equal employment opportunity will be extended to all persons in all aspects of the employer-employee relationship. This policy applies to all terms and conditions of employment, including, but not limited to, hiring, training, promotion, discipline, compensation benefits, and separation of employment. The Human Resources Department has overall responsibility for this policy and maintains reporting and monitoring procedures. Any questions or concerns should be referred to the Human Resources Department.