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Experienced Full Stack Data Scientist – Advanced Analytics and Machine Learning for Healthcare and Retail

Remote role Full-time Open position

Join the Walgreens Team and Revolutionize Healthcare and Retail with Data-Driven Insights

Are you a highly skilled data scientist with a passion for healthcare and retail? Do you want to work with a leading company that is dedicated to creating more joyful lives through better health? Look no further! Walgreens, a subsidiary of Walgreens Boots Alliance, Inc., is seeking an experienced full stack data scientist to join our team. As a data scientist at Walgreens, you will have the opportunity to work on cutting-edge projects that leverage advanced analytics and machine learning to drive business growth and improve patient outcomes.

About Walgreens and WBA

Walgreens (www.walgreens.com) is a leading healthcare, pharmacy, and retail company with a 170-year history of caring for communities. As part of Walgreens Boots Alliance, Inc. (Nasdaq: WBA), we are committed to creating more joyful lives through better health. With over 9,000 retail locations across the United States, Puerto Rico, and the U.S. Virgin Islands, Walgreens is proud to be a community health destination serving nearly 10 million customers every day. Our pharmacists play a vital role in the U.S. healthcare system by providing a wide range of pharmacy and healthcare services, including those that promote equitable access to care for the nation's medically underserved populations.

Job Responsibilities

As a full stack data scientist at Walgreens, you will be responsible for:

  • Building models and algorithms using technical expertise in machine learning, statistical modeling, and data science to provide insights and actionable recommendations
  • Understanding the business context behind large datasets and developing significant analytic solutions
  • Applying analytical rigor and statistical techniques to analyze large datasets, using advanced statistical methods such as predictive statistical models, customer profiling, segmentation analysis, survey design, analysis, and data mining
  • Building suggestions and optimization algorithmic designs, performing data retrieval, complexity analysis, and clinical computing
  • Programming using a tech stack that includes Python, PySpark, Matplotlib, TensorFlow, PyTorch, and other relevant tools
  • Performing data science strategies, and supervised and unsupervised algorithms to build predictive models and prescriptive solutions to support various business use cases
  • Building algorithms like decision trees, regression, XGBoost, K means, and anomaly detection
  • Utilizing Cloud Computing on Azure/Databricks, querying in Snowflake
  • Utilizing software tools and methodologies such as GitHub, Continuous integration and delivery, agile methodologies
  • Collaborating with finance, researchers, software developers, and business leaders to define product requirements and provide analytical support
  • Communicating verbally and in writing to business clients and management teams with diverse levels of technical expertise, educating them about our systems, and sharing insights and recommendations

Essential Qualifications

* Bachelor's degree and a minimum of 4 years of experience in data science, machine learning, quantitative or computational capabilities OR High School/GED and a minimum of 7 years of experience in data science, machine learning, quantitative or computational capabilities

  • M.S. in STEM, PC science, statistics systems, physics, mathematics, statistics, data science, machine learning, or similar
  • At least 4 years of experience working with large-scale, complex datasets to create/optimize machine learning, predictive, forecasting, and/or optimization models
  • Advanced experience in SQL, Python, PySPark or other languages
  • Advanced degree skills in exploratory data analysis, feature engineering and selection, detecting patterns, learning distributions, visualizing results, and extracting insights to help businesses make informed data-driven decisions
  • Experience using decision trees, and building classifiers
  • Experience with supervised machine learning techniques (linear and logistic regression, time series modeling, generalized linear models, decision trees, support vector machines, etc.) and unsupervised machine learning techniques (K means, hierarchical clustering, association rules, principal components)
  • Experience with Cloud ML systems, distributed computing, data pipelines, cloud data stores, and serving engines
  • Experience designing and analyzing A/B experiments
  • Advanced degree skills in conveying rigorous technical standards and issues to non-experts
  • Experience working in dynamic environments and working with ambiguity, prioritizing needs, and delivering results
  • Experience efficiently communicating technical solutions and advocating to data scientists, engineering teams, and business audiences
  • At least 2 years of experience contributing to business decisions in the workplace
  • At least 2 years of direct management, indirect management, and/or cross-functional team management
  • Willing to travel up to/at least 10% of the time for business purposes (within the country and out of the country)

Preferred Qualifications

* Ph.D. in STEM, PC science, statistics systems, physics, mathematics, statistics, data science, machine learning, or similar

  • Experience working with IoT, and Edge AI is a plus
  • Experience in Reinforcement Learning is a plus
  • Experience in Healthcare is a plus

Benefits

* Company-Paid Life Insurance

  • Medical, Prescription Drugs, Dental, and Vision
  • Retirement Savings Plan – 401(k)
  • Employee Stock Purchase Plan
  • Paid Time Off (PTO)
  • Holidays
  • Paid Parental Leave (PPL)
  • Transportation Benefit Plan
  • Employee Store Discount
  • Voluntary Life & Personal Accident Insurance

How to Apply

If you are a highly skilled data scientist with a passion for healthcare and retail, we encourage you to apply for this exciting opportunity. Please submit your resume and a cover letter explaining why you are the ideal candidate for this role. We look forward to hearing from you! Apply for this job

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