GameStop’s Marketing Analytics & Tech team is seeking a Lead Applied Data Scientist to help lead the Marketing Science division. With access to a wide variety of data across the organization, you will have the opportunity to influence the decision-making process and the marketing strategies for existing customers and marketing.
In this role, you will focus your efforts towards customer segmentation and behavioral framework, growth opportunities, customer development and retention efforts, media mix insights, measurement etc. You will derive hypotheses and validate through continuous experimentation and analysis while using statistical methods and ML framework.
Essential Job Duties and Responsibilities
- You will define a sustainable ML framework which starts and ends with a well-defined use case and a vision statement. You will focus on qualitative ML then quantitative ML and use simple and effective ML capabilities to drive growth
- You will Analyze and interpret media mix modeling results, develop deeper insights, and provide recommendations to the business
- You will define roadmap with strategic insights into different divisions like customer behavior, experience, and loyalty.
- You will manage the data science practices for business problems such as media mix modeling, cross-channel spend optimization, multi touch attribution, propensity, net lift, causal inference, etc. For such models, you will be responsible for the Data Science lifecycle from conception to prototyping, testing, deploying, and measuring the overall business value of the models. Also, you will manage the model health and the integrity of the underlying processes and assumptions.
- You use the data science and engineering to leverage new and existing machine learning models and help scale their usage across multiple use-cases
- You will proactively monitor existing metrics, develop, and propose new metrics, and work across the organization to make actionable intelligence available to business stakeholders
What You’ll Need:
- Advanced degree in analytical field (e.g. Applied Mathematics, Statistics, Data Analysis, Operations Research, Data Science)
- 4+ years of professional experience in data science and/or applied economics
- Demonstrated experience with the following: machine learning, data mining, computational analytics/optimization, application development, data mining, predictive modeling, deep learning
- Advanced proficiency in coding and data analysis using Python, SQL, R, SAS, or Scala
- Knowledgeable in using BigQuery, Cloud Dataproc, Google Data Studio, Cloud Dataflow, Spark, Hive, R, Python/Anaconda, TensorFlow a plus
- Experience working with Google Analytics, Salesforce Marketing Cloud is preferred