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Data Scientist II
  • Python
  • SQL
  • SAS
  • Machine Learning
  • Data Analysis
  • Data Mining
  • Modeling
GM Financial
Fort Worth, TX 76102
104 days ago
Overview:The Data Scientist II is responsible for implementing the design, development, deployment, and maintenance of predictive/prescriptive/statistical models; Modeling with expertise in forecasting, optimization, data mining, analysis, and analyzing complex datasets; Conducting studies with the use of descriptive and supervised machine learning methods and advanced statistical methods using innovative and the latest advanced technique and algorithms; Summarizing, reporting, and providing polished presentations of findings to a variety of internal clients as well as working with other departments to achieve the overall company objectives; Lead in the production of research and analysis to quantify the impact of internal and external environments on portfolio performance. The Data Scientist II is the subject matter expert with an in depth knowledge of quantitative methods and diligent knowledge of data sources and tools.Responsibilities:JOB DUTIES
  • Performs research, analysis, and modeling on organizational data
  • Assists in analyzing key metrics and performing data analysis
  • Builds technical knowledge to support research and analytic responsibilities including advanced techniques and algorithms
  • Conducts research projects, incorporate project design, data collection and analysis, summarizing findings, developing recommendations and effectively communicating to leadership the impact to the business
  • Develops and applies algorithms or models to key business metrics with the goal of improving operations or answering business questions
  • Presents findings and analysis for use in decision making
  • Ensures that the delivered products meet the business needs of the company
  • Partners with and provide recommendations to business leadership on the appropriate application of analytics to business strategies and effectively communicate analysis and implications to senior leadership
  • Prioritizes tasks and meets project deadlines in a fast paced work environment
  • Perform other duties as assigned
  • Conform with all company policies and procedures
Qualifications:Knowledge
  • Ability to identify and understand business issues and map these issues into quantitative questions
  • Advanced knowledge and demonstrated understanding of applied methodologies including least squares regression, logistic regression, sampling methodologies, time series, survival analysis, cluster analysis, categorical data analysis, decision trees, multivariate methodologies, non-parametric techniques, principal components, and linear programming techniques
  • Advanced skills in Python, SAS, SQL, R, JMP, Excel, Word, PowerPoint
  • Ability to design and implement model documentation and monitoring protocols
  • Demonstrated understanding and experience with technical systems, datasets, data warehouses, and data analysis techniques
  • Efficiently work with large datasets
  • Strong quantitative, analytical and data interpretation skills with a solid foundation of mathematics, probability, and statistics
Skills
  • MS Office required
  • Proficient in Python or SAS required
  • Strong written and verbal presentation skills with an ability to communicate effectively with Senior Management by making complex concepts easy to understand
  • Ability to be curious, ask questions, explore, and be creative when analyzing data and business problems
  • Ability to identify and seek needed information/research skills
  • Analytical thinking skills
  • Ability to interact collaboratively with internal and external customers
  • Capable of managing multiple and varied projects, including the ability to coordinate and balance numerous tasks in a time-sensitive environment, under pressure
  • Strong problem solving skills
Education
  • Master’s Degree in Statistics, Applied Mathematics, Econometrics, Economics, Operations Research, Industrial Engineering, Computer Science, or similar quantitative field required
Experience
  • 2-4 years as Data Scientist or similar quantitative field required
Working Conditions
  • Normal office environment

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