Preferred Qualifications
- 5 to 7 years of experience in applied data science in a retail marketing or operations environment.
- 5+ years of quantitative and analytics experience.
- Management experien
- Master's degree in mathematics, statistics, computer science, or a related field.
- Strong understanding and application of statistical methods and skills: distributions, experimental design, variance analysis, A/B testing, and GLM/ Regression.
- Expertise in machine learning algorithms and experience using the following ML techniques: Logistic Regression, Decision Trees, Random Forests, Gradient Boosting, SVMs, Time Series, KMeans, Clustering, Recommendation Systems
- Strong coding and debugging skills in one or more of the following technologies: Python, R, Pandas, Scikit-learn, PySpark.ML
- Advanced knowledge of SQL and proven experience with large data sets such as Hadoop, hive, spark
- Strong skills in developing recommendation engines / collaborative filtering or developing models for supply chain optimization a plus
- Experience visualizing/presenting data for stakeholders using any of the following: Tableau, PowerBI, ggplot, etc.
- Must have a proven track record of partnering with business in delivering quality business solutions
- Strong collaboration skills with both technical and non-technical groups
- Appropriately account for the timeliness and quality of all assignments
- Manage multiple projects concurrently
- Prioritize and monitor project progress relative to timeline and scope
- Experience deployment models into production and designing APIs for model consumption, Azure ML and building data pipelines - a plus
- Experience with mathematical programming languages and optimization software - a plus
- Experience with Neural Networks (RNNs/CNNs) and deep learning libraries such as Tensorflow, Theano, Keras - a plus
- Natural language processing (NLP), social network analysis - a plus
Job Summary
Responsible for managing team efforts to develop easily repeatable reports and dashboards that allow internal clients to make data-driven decisions. Implements strategies that result in measurable financial returns. Works with various business stakeholders to develop insights and understand customer data.
Major Tasks, Responsibilities, and Key Accountabilities
- Tests, analyzes, and solves data issues to ensure data integrity. Provides technical support for end users of the self-service business intelligence tool.
- Develops complex reporting dashboards and scorecards. Reports and analyzes data for all areas of the business to drive results and guide business intelligence decisions.
- Collaborates with Sales, Marketing, Customer Care, and Strategy to target insights and understand customer behavioral data.
- Provides support to multiple departments to ensure that business intelligence, analytics, and reporting needs are met and delivered through technology, architecture, processes, and tools.
- Manages project communications between all departments. Communicates directly with team members to monitor scheduled deliverables, relay revision requests, record progress, and address obstacles as needed.
- Designs and manages multivariate and/or A/B testing for marketing and web evolution.
Nature and Scope
- Solutions require analysis and investigation.
- Achieves planned results by decisions and actions based on professional methods, business principles, and practical experience.
- Manages a group or team of professional individual contributors and/or indirectly supervises support staff.
Work Environment
- Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.
- Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light articles.
- Typically requires overnight travel 20% to 50% of the time.
Education and Experience
- Typically requires BS/BA in a related discipline. Generally 7+ years of experience in a related field. May require certification. Advanced degree may offset less experience in some disciplines.
