Data Scientist

Requirements

• Master’s degree or foreign equivalent degree in Statistics, Applied Mathematics, Economics, Engineering, Computer Science, or a related field and one year of experience in the job offered or a related occupation
• Employer will accept a Bachelor’s degree or foreign equivalent degree in Statistics, Applied Mathematics, Economics, Engineering, Computer Science, or a related field and five years of progressive post-baccalaureate experience in the job offered or a related occupation as equivalent to the Master’s degree and one year of experience
• Must have one year of experience in the following skill(s): (1) building statistical models and machine learning models using large datasets from multiple resources; (2) writing SQL scripts for analysis and data migration; and (3) applying specialized modelling software including R, Python, or MATLAB

• Design and implement scalable and reliable approaches to support or automate decision making throughout the business
• Apply a range of data science techniques and tools combined with subject matter expertise to solve difficult business problems and cases in which the solution approach is unclear
• Acquire data by building the necessary SQL / ETL queries
• Import processes through various company specific interfaces for accessing Oracle, Red Shift, and Spark storage systems
• Build relationships with stakeholders and counterparts
• Analyze data for trends and input validity by inspecting univariate distributions, exploring bivariate relationships, constructing appropriate transformations, and tracking down the source and meaning of anomalies
• Build models using statistical modeling, mathematical modeling, econometric modeling, network modeling, social network modeling, natural language processing, machine learning algorithms, genetic algorithms, and neural networks
• Validate models against alternative approaches, expected and observed outcome, and other business defined key performance indicators
• Implement models that comply with evaluations of the computational demands, accuracy, and reliability of the relevant ETL processes at various stages of production