Experience qualifications 2 years of experience as Analyst or any occupation in which the required experience was gained, and demonstrated experience in: Business analysis; Reporting and data analysis for sales or service teams; Advanced MS Excel and PowerPivot skills to model large amounts of data; Data visualization and reporting on Tableau or Microsoft Power BI; Statistics and forecast modeling; Statistical and descriptive concepts and methodologies; SQL or related data querying and manipulating tool; Strong knowledge of quantitative analysis using Python; Pulling and analyzing data from complex and big data sources; Strong economic and market analysis skills; Strong analytical skills with work experience in dynamic environment; Demonstrated ability to solve and to lead others in solving complex analytical problems; Competitive analysis; Database management systems, data structuring, and data architecture; Machine learning methods including correlation, clustering, segmentation, and regression; Machine learning algorithms including XGboost, KNN Neighbors, and Random Forest; Data extraction, cleaning, and analysis; Cloud Computing or Distributed Computing; Azure Databricks or Spark. Data Scientist to perform the following duties: Gather data from various analytical databases and sources, and implement advanced statistical methodologies to optimize operations; Obtain, manipulate, clean, and analyze structured and unstructured data from diverse sources; Conduct exploratory analyses including hypothesis testing, statistical inference and statistical analysis (predictive and/or prescriptive); Partner with business and technical stakeholders to translate challenging retail business problems into state-of-the-art data science solutions; Work with other teams across the organization to integrate and centralize customer data for analytics purposes to increase customer knowledge across the organization, including but not limited to third party data, digital behavior, operational metrics, etc.