Dollar General Corporation has been delivering value to shoppers for more than 80 years. Dollar General helps shoppers Save time. Save money. Every day.® by offering products that are frequently used and replenished, such as food, snacks, health and beauty aids, cleaning supplies, basic apparel, housewares and seasonal items at everyday low prices in convenient neighborhood locations. Learn more about Dollar General at .
DUTIES and ESSENTIAL JOB FUNCTIONS: 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); develop dynamic, productionized, and scalable customer-level models that generate ROI for both DG and their customers (these models may include predictive propensity models and customer segmentations); serve as a leader on the team providing direction, sharing knowledge, offering analytical expertise, and mentoring junior team members as appropriate; apply strong problem-solving skills utilizing expertise, business judgement, and robust quantitative analyses; develop code to combine, clean, and prepare data for modeling, using some combination of SQL, Python, and PySpark (including but not limited to pandas, numpy, scikit-Learn, matplotlib); identify and implement proper data preparation and feature engineering methods, such as outlier identification and removal, principal components analysis (PCA), and general data structuring; apply experience with common modeling techniques, such as logistic regression, decision trees, random forest, SVM, regularized regression, and natural language processing (NLP); demonstrate ability to translate complicated analytics topics into easily communicable concepts to less technical audience, including model accuracy and feature importance; apply practical experience ingesting and manipulating large volumes of data (millions of records); demonstrate proficiency with common analytical platforms, including distributed compute (e.g. Databricks, Hadoop, Snowflake, etc.) and PowerBI. Telecommuting/hybrid work permitted up to 3 days per week from a home office location within normal commuting distance from Goodlettsville, TN office.
Master's degree (U.S. or foreign equivalent) in Data Science, Statistics, Economics, Computer Science, Mathematics, or related applied quantitative field; 5 years of work experience in Data Science & Analytics; 3 years of developing or leading development of statistical models; and Experience with the following: (i) applying statistical machine learning techniques to predictive modeling; (ii) Machine Learning libraries; (iii) developing code to combine, clean, and prepare data for modeling using some combination of SQL, Python and PySpark; (iv) identifying and implementing proper data preparation and feature engineering methods; (v) modeling techniques such as logistic regression, decision trees, random forest, SVM, regularized regression, and natural language processing (NLP); (vi) ingesting and manipulating large volumes of data; (vii) analytical platforms, including distributed compute (e.g. Databricks, Hadoop, Snowflake) and PowerBI; (viii) code management tools such as Github; and (ix) customer-level modeling. Telecommuting/hybrid work permitted up to 3 days per week from a home office location within normal commuting distance from Goodlettsville, TN office.
