Data Science Intern
Position Summary
The Data Science Intern is a statistical and/or economics specialist who is primarily responsible for data mining, data munging, and in all ways extracting data from disparate data sources for the purposes of modeling and deep analytics. In short, this person will need to feel comfortable with several aspects of Data Science – can pull the data, clean it, perform modeling, create visualization as well as interpret the results and explain the thought process.
Essential Functions/Responsibilities:
The Major Responsibilities Include
- Partnering with the business to identify deficiencies in data mining and creating solutions to remedy the deficiencies (in other words democratize the company data in consumable ways)
- Create SQL queries that can be used by non-technical business partners in order to help them with their reporting and analysis work
- Partner with senior members of the team on a variety of modeling (clustering, time series, regression, etc.)
- Willingness to train other team members in SAS, SQL, R, and Python
- Respond to ad hoc forecast inquiries from executive, merchant, planning and finance teams
- Conduct variance analysis of actual to forecasted performance in order to identify business trends, risks and opportunities and provide meaningful internal reporting
- Utilize analytical and mathematical skill sets on a daily basis to improve the overall accuracy of the models
- Be able to work with a high degree of autonomy while maintaining a focus on project deadlines associated with dependent business processes
- Translate technical findings into meaningful business information
- Research white papers to find the best statistical approaches for the assigned projects
- Stay up to date on retail industry trends
Requirements/Qualifications:
Position Requirements
Education: Majoring in Math, Statistics, Economics with relevant work experience in analytics
Software: SAS, Python, R, SQL/MySQL, Tableau, Teradata SQL Assistant
Statistical Methods: ANOVA, Regression, Time series, Logit/Probit models, Principal Components Analysis and Dimensionality Reduction
Machine Learning:Classification, Regression, Clustering
General Skills:
- Self-motivated and team oriented
- Ability to work in a fast paced and continuously evolving environment
- Ability to interpret technical and quantitative forecast models into meaningful content that the business users can consume
- In-depth analytical skills and knowledge
- Well-organized with attention to detail
- Good communication skills