2019 Enterprise Analytics Summer Intern (Machine Learning & Advanced Modeling)
The Enterprise Analytics team exists to equip and empower informed decision making through data and analytics.
Who are we looking for? It may be you, if you answer "yes" to the following questions.
- Are you a creative thinker who can deliver innovative approaches to solve problems through the use of data?
- Are you a detail-oriented person that likes working with data, models, mining and visualization of information?
- Are you a researcher, who loves to ask questions and investigate?
- Are you a good communicator capable of transforming numbers into knowledge and action in a way that is easily understood?
If you are passionate about modeling complex business problems, discovering insights and identifying opportunities through the use of statistical, algorithmic, mining, simulation and visualization techniques, then this position is for you! The mission of this position requires a multidisciplinary blend of statistics, technology, and business strategy, all applied in tandem to discover and pave the path for the future of analytics at
The successful Enterprise Analytics Intern (MLAM) will be able to:
- Analyze quantitative data and develop models or simulations for complex problems in order to answer some of the most important business questions
- Perform analysis around bottlenecks / constraints and recommend changes to maximize capacity and throughput
- Understand and apply data mining and visualization techniques to better understand current state and make recommendations to impact the desired state
- Work closely with clients, data stewards, project/program managers, IT, and the internal Enterprise Analytics team
- Identify what data is available and relevant or what data needs to be collected in order to best answer key business questions
- Present findings to business stakeholders in a way that can be easily understood and acted upon
- Strong academic track record supported by GPA (Min 3.2)
- Pursuing a degree in Statistics, Analytics, Engineering, Operations Research, or a related quantitative or technical discipline
- Experience with SAS, SPSS, or R (SAS preferred) or other applicable programming languages
- Experience with Tableau, Alteryx, Redshift, or other data visualization or data processing tools
- Strong analytical and research skills
- Excellent oral and written communication skills
- Ability to learn things quickly and work independently. Analytical, creative, and innovative approach to solving difficult problems
- Currently pursuing an advanced degree in Business, Statistics, Engineering, Operations Research, or another quantitative or technical discipline.
- 3-5 years of experience in analytics
Required Level of Education
Preferred Level of Education
Statistics, Analytics, Engineering, Operations Research, or a related quantitative or technical discipline
Minimum GPA (4.0 Scale)
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