Data Scientist

Walgreens•Deerfield, IL

About The Position

The Data Scientist applies advanced statistical, analytical, and machine-learning techniques to solve business problems and support Marketing, Loyalty, and CRM decision-making. The role works with large, complex datasets to develop predictive models, conduct exploratory and statistical analyses, evaluate business outcomes, and identify opportunities to improve customer engagement and marketing effectiveness. The Data Scientist prepares and integrates data, selects appropriate analytical methods, validates results, and translates findings into clear, actionable recommendations. The position also documents projects and presents interpretations of findings to internal clients and business audiences.

Requirements

Bachelor's degree and at least 2 years of experience in quantitative or computational functions, or a graduate degree in a quantitative, computational, or technical discipline.
Knowledge of SQL.
Experience in data science, advanced analytics, or statistics, with the ability to interrogate and analyze data, interpret results, and present findings to business audiences.
Knowledge of open-source data science and statistics packages such as Python, R, or Spark.
Experience establishing and maintaining key relationships with internal peers, business partners, and leadership, and external business-community contacts, clients, and vendors within a matrix organization.
Experience analyzing and reporting data to identify issues, trends, or exceptions, drive improved results, and find solutions.
Willingness to travel up to 10% of the time for business purposes, within and outside the state.

Nice To Haves

Graduate degree in statistics, economics, data science, applied mathematics, computer science, engineering, or a related quantitative discipline.
Strong proficiency in SQL and Python or R, including experience manipulating and analyzing large datasets.
Knowledge of statistical modeling, machine learning, experimental design, and model evaluation techniques.
Experience with data preparation, feature engineering, exploratory analysis, and data visualization.
Ability to write clear, reusable, and well-documented analytical code.
Strong analytical problem-solving and communication skills, including the ability to explain technical findings to nontechnical audiences.
Experience in marketing, customer, CRM, or loyalty analytics.

Responsibilities

Apply advanced data analysis tools and techniques to provide business insights and actionable recommendations, using complex statistical modeling to predict future outcomes across multiple scenarios.
Interpret and apply data in complex analyses, and explain findings to business audiences to improve products and processes.
Support or lead the development of data-related commercial offerings and other intellectual property.
Execute statistical and mathematical analyses to support business decision-making.
Develop or use algorithms and statistical predictive models, and determine analytical approaches and modeling techniques to evaluate scenarios and potential future outcomes.
Analyze large amounts of data using advanced statistical techniques, including predictive statistical models, customer profiling, segmentation analysis, survey design and analysis, and data mining.
Document projects, including business objectives, data gathering and processing, leading approaches, final algorithms, results, and analytical metrics.
Develop materials explaining project findings.
Resolve problems and roadblocks as they occur.
Exchange semi-complex information about assigned activities with internal and external peers and/or managers.
Prepare and present interpretations of findings to internal clients.