Principal Data & Machine Learning Scientist (WH)

Key Skills

AutoGluon, Caffe, CDASH, Databricks, Design of Experiment, Distributed systems, Docker, Java Programming, Keras software library, matplotlib, Natural Language Processing (NLP), Python Programming, PyTorch, Scikit-learn, SQL, TensorFlow, VR/AR frameworks

Job Description

The Principal Data & Machine Learning Scientist is responsible for applying highly complex and industry-leading data analysis tools and techniques to provide insights and actionable recommendations for the business. The individual will utilize highly complex statistical modeling to make predictions about future outcomes and in multiple scenarios, and will explain findings to business audience including executives. You are expected to deliver innovative, high-quality solutions aligned with our mission and to foster a culture of collaboration, trust, and technical expertise.

Job Responsibilities

• Leads in the design and development of highly complex and innovative scalable algorithms and models for solving various business problems and driving value for Walgreens Boots Alliance, drawing from knowledge and experience in Machine Learning/AI, constrained optimization, probabilistic theory, statistical theory, graph theory, or related fields. Application areas include but are not limited to algorithmic process of recommendation for patient health/outcome improvement, automation; optimization; demand forecasting; outlier detection, mathematical optimization, cost to serve optimization; natural language processing, marketing intelligence; and personalization.
• Collaborates with business clients, product managers, data engineers, front end developers, and other team members to build and deploy scalable ML/AI infused applications, or other data centric products that incorporate constrained optimization, multi-dimensional recommenders, statistical theory, large-scale forecasting, sensor analytics, IoT, etc.
• Programs using tech stack Python, PySpark, Matplotlib, TensorFlow, PyTorch, etc.
• Utilizes Cloud Computing on Azure/Databricks, querying in Snowflake.
• Develops and executes on ML/AI strategies and plans.
• Performs machine learning techniques, supervised and unsupervised algorithms
• Works with key stakeholders to formulate a comprehensive plan that is consistent with the overall business objectives and budgetary considerations.
• Applies broad knowledge of ML/AI capabilities to identify new growth areas, new and emerging opportunities.
• Conducts research by studying organization goals, strategies, practices, and user cases.
• Recommends strategies by evaluating organization outcomes; identifying problems; evaluating trends; anticipating requirements.
• Shares highly complex and innovative information related to areas of expertise.
• Interacts with executives and senior management to keep abreast of objectives. Interacts with peers to interpret information and improve cross-functional processes and programs. Builds and enhances key internal and external contacts.
• Mentors and develops less experienced ML Scientists
• Provides thought leadership to embrace modern AI/ML, data science and data analytics techniques as critical enablers for business decisions.

An Equal Opportunity Employer, including disability/veterans

About Walgreens Boots Alliance

Walgreens Boots Alliance (Nasdaq: WBA) is a global leader in retail pharmacy, impacting millions of lives every day through dispensing medicines, and providing accessible, high-quality care. With more than 170 years of trusted healthcare heritage and innovation in community pharmacy, the company is meeting customers’ and patients’ needs through its convenient retail locations, digital platforms and health and beauty products.

Including equity method investments, WBA has a presence in more than 25 countries, employs more than 450,000 people and has more than 21,000 stores.

WBA’s purpose is to help people across the world lead healthier and happier lives. The company is proud of its contributions to healthy communities, a healthy planet, an inclusive workplace and a sustainable marketplace. WBA is a participant of the United Nations Global Compact and adheres to its principles-based approach to responsible business.

WBA is included in FORTUNE’s 2021 list of the World’s Most Admired Companies*. This is the 28th consecutive year that WBA or its predecessor company, Walgreen Co., has been named to the list.

More company information is available at www.walgreensbootsalliance.com.

Basic Qualifications

• Bachelor’s Degree and at least 8 years OR High School/GED + at least 11 years of experience in STEM, computer science, information systems, physics, mathematics, bio or statistics, computational chemistry, data science, machine learning, artificial intelligence or similar.
• M.S. degree
• Expert level skill in at least one general purpose programming language, such as Python, PySpark, C#/C++, etc.
• At least 6 years of experience working with large-scale, complex datasets to create/optimize machine learning, predictive, forecasting, and/or optimization models.
• Expert level skill in SQL or any other relational and non-relational databases.
• Expert level skill in exploratory data analysis, feature engineering and selection, detecting patterns, analyzing distributions, visualizing results, and extracting insights to help business make informed data driven decisions
• Experience with NLP
• Experience with non-relational databases
• Experience and knowledge of distributed / parallel computing
• At least 5 years of experience contributing to financial decisions in the workplace.
• At least 5 years of direct leadership, indirect leadership and/or cross-functional team leadership.
• Willing to travel up to 10% of the time for business purposes (within state and out of state).

Preferred Qualifications

• Ph.D. degree in Computer Science, Statistics, Artificial Intelligence, Machine Learning, Physics, Mathematics, Computational or Decision Sciences, computational chemistry or a related quantitative field.
• Experience using decision trees, building classifiers.
• Experience with supervised learning methods (linear and logistic regression, time-series modelling, generalized linear models, decision trees, support vector machines, etc.) and unsupervised learning methods (K-means, hierarchical clustering, association rules, principal components). Experience with Neural Networks, Natural Language Processing, and optimization algorithms.
• Experience with Cloud ML platforms, distributed computing, data pipelines, cloud data stores and serving engine.
• Experience designing and analyzing A/B experiments.
• Expert level skill in conveying rigorous technical concepts and considerations to non-experts.
• Experience working in a dynamic environment and working with ambiguity, prioritizing needs, and delivering results.
• Experience effectively communicating technical solutions and advocating to research scientists, engineering teams and business audiences.
• Experience with Pandas, Scikit-learn, Matplotlib, NLTK or similar libraries and with TensorFlow, Keras or PyTorch, Caffe/Caffe2, Gluon, Dash, or Flask frameworks.
• Expert level skill with Azure Blob Storage Azure HDInsight, Azure Databricks, Azure Kubernetes Service, or any other Cloud environment.
• Experience in cloud deployment of ML/AI applications.
• Experience working with IoT, and Edge AI is a plus.
• Experience in Reinforcement Learning is a plus.
• Experience in Healthcare is a plus.
• Advanced level skill in the following:
• Keras/Tensorflow or Pytorch
• Collaborative Filtering
• NLP / Image processing
• BERT/ELMo embeddings
• Deep Neural Networks
• Layers: CNN, RNN: GRU/LSTM
• Transfer learning
• Reinforcement Learning
• Recommendation engines
• Algorithmic complexity
• Linux development environments / shell scripting
• Distributed / parallel computing Databricks.
• SQLAlchemy, non-relational databases.
• Software testing procedures
• Software design principles such as SOLID
• Software design patterns
• Docker