Description
Work Where You Matter: At Dollar General, our mission is Serving Others! We value each and every one of our employees. Whether you are looking to launch a new career in one of our many convenient Store locations, Distribution Centers, Store Support Center or with our Private Fleet Team, we are proud to provide a wide range of career opportunities. We are not just a retail company; we are a company that values the unique strengths and perspectives that each individual brings. Your difference truly makes a difference at Dollar General. How would you like to Serve? Join the Dollar General Journey and see how your career can thrive. Company Overview:
As a Lead Data Scientist with Dollar General, you'll develop models and algorithms for our retail business. You'll work closely with Asset Protection and Store Operation teams to continuously learn more about our business and develop an understanding of the various business processes. You will oversee the creation and development of key reports and analytical models that will help optimize processes and improve efficiencies, especially related to missing and damaged product.
Job Details:- Develop and maintain production grade dashboard reporting processes, collaborating with end-users to intake requirements and IT partners to establish reliable, automated pipelines.
- Perform analytical tasks that include data gathering, analysis, visualization, and data-driven storytelling as a basis of project justification and innovation.
- Perform statistical/machine learning projects as necessary for given business needs. These projects may consist of – large scale/rapid hypothesis testing, classification, prediction, and recommender systems.
- Serve as a leader on the team providing direction, sharing knowledge, offering analytical expertise, and mentoring junior team members as appropriate.
- Strong problem-solving skills utilizing expertise, business judgment and robust quantitative analyses
- Practical experience ingesting and efficiently manipulating large volumes of data (millions of records)
- Develop code to combine, clean, and prepare data for reporting/modeling using some combination of SQL, Python and PySpark (including but not limited to pandas, numpy, scikit-Learn, matplotlib, tensor- flow)
- Ability to translate complicated analytics topics into easily communicable concepts to less technical audiences, including model accuracy and feature importance
- Identify and implement proper data preparation and feature engineering methods, such as outlier identification and removal, principal components analysis (PCA), and general data structuring
- Knowledge of statistical and modeling techniques/concepts (properties of distributions, statistical tests logistic regression, decision trees, random forests, etc.)
- Proficiency with common analytical platforms, including distributed compute (e.g. Databricks, etc.) and data visualization tools (PowerBI)
- Experience with code management tools such as Gitlab
- Experience with CI/CD automated processes preferred
- Experience with Store Operations and Asset Protection concepts such as shrink and damages preferred
- Experience mentoring junior team members preferred
- MS in Data Science, Statistics, Economics, Computer Science, Mathematics, or related applied quantitative field preferred.
- 8+ year's hands-on industry (non-academic) experience in Data Science (or equivalent quantitative job title). Strong background in building efficient data-driven processes and applying statistical techniques
- 3-4 years of developing /automating reporting processes and statistical model
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