Sr Data Scientist, Measurement & Reporting

Key Skills

Apache Hadoop, Continuous Integration & Continuous Delivery - CI/CD, Databricks, Decision trees, Large data sets, Logistic Regression, Machine learning techniques, matplotlib, Natural Language Processing (NLP), Neural Networks, NumPy, Pandas, PowerBI, Predictive analytics, Predictive Modeling, PySpark, Python Programming, Random forests, Scikit-learn, Snowflake, SQL, Statistical modeling, SVN, Tableau, TensorFlow

Job Description

Lead Data Scientist -for testing and measurement roles give a chance to help develop Dollar General in-house strength for quantifying the impact or minimizing the risk for a broad range of initiatives such as Marketing campaign

DUTIES and RESPONSIBILITIES:

• Responsible for conducting advanced analysis of marketing campaigns from both structured and unstructured data to better understand marketing opportunities. 30%
• Design, develop and evaluate advanced predictive and machine learning models with a focus on the optimization of marketing tactics and the customer journey within campaigns, products, and events. 30%
• Conduct advanced analysis on various marketing efforts to gauge performance, impact, and effectiveness against the desired results. 10%
• Deliver clear and compelling findings with data visualization tools and presentations that inform and inspire internal stakeholders to make better business decisions. 10%
• Collaborate with colleagues in Marketing Operations and IT to infuse predictive analytics into customer touchpoints, driving increased relevance and business performance. 10%
• Design and deliver insights using a mixture of analytical and visualization techniques. Additionally, define the approach, develop the roadmap and lead ongoing review routines. 10%

Qualifications

KNOWLEDGE and SKILLS:

• You are an expert in research areas such as measuring bias and machine learning
• You have deep applied experience with the customer predictive model process, including attribute screening, using 1st party data attributes and the overall scoring process
• You understand how to identify model bias, predictor drift and best practices for reporting on both
• You are competent in programming with statistical modeling tools to fuel and deliver marketing personalization and business insights.
• You have a strong familiarity with manipulating and mining data to transform business decisions that impact the bottom line. 
• You have knowledge in leveraging visual analytics to create a seamless and inspirational story that inspire and inform business leaders with the necessary knowledge to drive revenue and customer loyalty.

Experience/Knowledge in the following areas preferred:

• Retail, Digital Media Network
• Marketing Personalization
• Marketing Mix Models, attribution, forecasting, and market testing
• Digital Marketing & Analytics
• Business Intelligence Reporting
• CRM Execution
• Consumer Research and Journey
• Consumer Data
• Competitive Analysis

EXPERIENCE and/or EDUCATION:

• MS in Data Science, Statistics, Economics, Computer Science, Mathematics, or related applied quantitative field preferred. Bachelor’s in a highly quantitative/STEM field considered with the right experience.
• 2-5 years hands-on industry (non-academic) experience in Data Science (or equivalent quantitative job title). Strong background in applying statistical machine learning techniques to predictive modeling and experience with Machine Learning libraries