설명
Develop new mathematical and statistical models and concepts, including multivariate regression, hierarchical Bayes, random forests, decision trees, and nonparametric statistics, to solve critical and strategic business problems relative to automotive product quality, design, engineering, Service, marketing, sales, and other forecasting. Determine type, structure, and source internal and external data needed to apply developed statistical model and concepts to answer critical and strategic business questions efficiently and accurately. Analyze, cleanse, and organize data pulled from internal Hadoop and external cloud environments using techniques including fuzzy matching and data profiling techniques. Apply knowledge of the business problem and other technical details to impute and build a comprehensive Analytical Data Set. Research current industry technical solutions that have been developed to address similar problems to benchmark mathematical model development options under consideration. Compile and apply mathematical theories and techniques using computer-driven mathematical analysis tools, including mathematica mathematical symbolic computation, python numerical and statistical software packages, R statistical computing tool and packages, and others to solve practical problems in automotive processes such as Product Quality, Design, Engineering, service, marketing, sales. Design experiments to develop and implement analytic and statistical prediction models in controlled and confined markets; analyze outcome of experiments using developed and standard statistical analyses. Design surveys and opinions clinics and use existing surveys and opinion polls as data sources for statistical models to address strategic business goals and imperatives. Create coherent conclusions and business insights from the models’ results of analyses and suggest actionable measures. Develop data analyses to support and improve business decisions based on statistically sound rulings using analytical methods and model averaging techniques. Draw conclusions and make predications based on mathematical analysis of complex, voluminous empirical data to drive effective business best practices and solutions. Conduct technical knowledge transfer to IT operations team members and support operations team to implement in production mathematical models to support daily business decsions.
[Additional Description]
REQUIREMENTS:
Bachelor’s degree in Statistics, Mathematics, Data Science or related field of study. Four (4) years of experience as a Senior Data Scientist, Data Scientist, Statistician or related occupation. Four (4) years of experience with: Data Science: Advanced Analytics techniques including artificial intelligence techniques including various types of neural nets; Machine Learning and Statistical methods including regression, probability analysis, risk analysis, and statistical process control; Data gathering, inspecting, cleansing, transforming, mapping, and modeling diagramming techniques; Databases: Databricks, Azure, Oracle, SQL Server MS Access; and Data integration: SQL, NoSQL, Hadoop, Cassandra, Alteryx, and Trifacta. One (1) year of experience with: Business Intelligence and Reporting Tools: Tableau, Power BI, Excel, JMP, SAS, SPSS, and Cognos.
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다양성 정보
General Motors는 법적으로 금지된 차별을 배제하는 것은 물론 포용성과 소속감을 진정으로 장려하는 직장이 되기 위해 노력하고 있습니다. 당사는 다양성이 보장되는 환경에서 직원들이 역량을 발휘하고 우리 고객을 위한 더 좋은 제품을 개발할 수 있다고 믿습니다. 따라서 입사에 관심 있는 사람이 있다면 포지션별 주요 업무와 자격을 확인하고 본인이 보유한 기술과 능력에 부합하는 모든 포지션에 적극적으로 지원하기를 장려합니다. 지원자는 채용 과정에서 역할 관련 평가(해당하는 경우) 및/또는 채용 전 스크리닝을 통과해야 합니다. 자세한 정보는 GM 채용 과정 안내를 참고하십시오.
공평한 취업 기회 선언 (미국)
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숙소 (미국 및 캐나다)
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