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Development Data Scientist
  • Python
  • Spark
  • SQL
  • Machine Learning
  • Data Analysis
  • Data Visualization
  • Modeling
  • Scala
  • Bayesian
  • XGBoost
Paycom
Oklahoma City, OK 73103
107 days ago
Job DetailsLevelExperiencedJob LocationOklahoma City Office - Oklahoma City, OKPosition TypeFull TimeEducation LevelBachelor's DegreeJob CategoryInformation TechnologyDescription

Conduct data analysis and build machine learning models for internal and client-facing applications.

RESPONSIBILITIES

  • Mine and analyze complex and unstructured data sets using advanced statistical methods including linear regression, logistic regression, decision trees, Bayesian methods, gradient boosting, and neural networks.
  • Perform research, analysis, and statistical modeling using the above methods.
  • Test and validate predictive models.
  • Develop methods of relaying interpretation of data using means including software, models, and graphs
  • Identifies unique opportunities to collect new data by recognizing key metrics that may be predictive of a particular business outcome, but that are not currently captured by existing processes. These data may be captured from transformations of other existing data sources, launches of new applications, or from external sources
  • Processes used include writing scripts and functions to accomplish tasks such as gathering data from various internal sources, performing large scale data transformations, analyzing key relationships between data, and building models to make predictions of future outcomes
  • Performs research, analysis, and statistical modeling on organizational data
  • Develops and applies algorithms or models to key business metrics with the goal of improving operations or answering business questions
  • Interprets data to identify business trends, conduct root cause analysis of business problems, or suggest areas for process improvement
  • Implements new or enhanced software designed to access and handle data more efficiently.
  • Provides data stories by using data visualization and data communication techniques
Qualifications

Education/Certification:

  • Bachelors in Computer Science, Data Science, Business Analytics or similar quantitative field.
  • Preferred: Masters in Computer Science, Data Science, Business Analytics or similar quantitative field.

Experience Required:

  • Preferred 1-3 years of experience

Skills/Abilities:

  • Required: R and/or Python; SQL; statistical analysis and modeling, including linear and generalized linear models; time series analysis and forecasting; machine learning models such as random forests, XGBoost, and SVM.
  • Preferred: Spark (in Scala or from R or Python); Neural networks, including CNN and RNN architectures; Natural language processing, including topic modeling, intent & entity extraction, and building domain-specific language models.

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.

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