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- Understand strategic business objectives and work with business partners to economically justify and develop plans to create the necessary business insights.
- Guide and inspire the organization about the business potential and strategy of data science.
- Utilize a combination of business acumen and statistical knowledge to identify, prioritize, and solve high-impact business problems.
- Translate complicated concepts into relevant business messages. Effectively communicate results to project stakeholders and business teams.
- Proficiency in the Azure Machine Learning platform to develop ML solutions
- Collaborate with ML operations, data engineers, and IT to evaluate and implement ML deployment options
- Integrate model performance management tools into the current business infrastructure
- Selecting features, building, and optimizing classifiers
- Identify, visualize, and analyze data from a variety of sources to obtain business insights.
- Outstanding storytelling skills to deliver results to senior management
- Educate business partners on the use and expected results of advanced analytics.
- Lead and manage analytical projects from conceptual through definition phase.
- Experience participating actively in Agile development and product teams.
- Display drive and curiosity to understand the business process to the core
- Bachelor's degree in Computer Science, Information Systems, Mathematics, or related required
- Master's degree with an emphasis in Statistics, Data Science, Mathematics, Computer Science or related preferred
- 5 or more years of experience in statistics, mathematics, machine learning or similar field required
- Experience solving analytical problems using quantitative approaches.
- Familiarity with relational and non-relational databases
- Experience with manipulating and analyzing complex, high-volume, high-dimensional data from varying sources.
- Experience with Microsoft AzureML
- Experience with data cleansing, preparation, and featurization and selection techniques
- Experience with data science projects from data management, model building, evaluation, model improvement and implementation.
- Experience with Agile development and Agile tools
- Fluency in advanced analytics tools such as R and Python.
- Understanding of Machine Learning techniques and Statistical learning methods.
- Applied statistical skills, such as distributions, statistical testing, regression and more.
- Strong written, verbal communication, and time management skills.
- A flexible analytic approach that provides results at varying levels of precision.
- Ability to communicate complex quantitative analysis in a clear, precise, and actionable manner.
- Ability to generate positive business results via analytics and data science techniques.
- A strong passion for empirical research and answering difficult questions with data.