Associate Data & Machine Learning Scientist (WH)

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

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

Job Responsibilities

• Assists in developing and deploying 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.
• Utilizes Cloud Computing on Azure/Databricks, querying in Snowflake.
• Assists in performing machine learning techniques, supervised and unsupervised algorithms.
• Preprocess data, performs statistical and multivariate analysis, feature importance analysis and feature engineering, research what model to choose.
• Conducts research by studying organization goals, strategies, practices, and user cases.
• Interacts with peers to interpret information and improve cross-functional processes and programs. Builds and enhances key internal and external contacts.
• Escalates problems and roadblocks as they occur to senior level scientists

Basic Qualifications

• Bachelor’s Degree and at least 1 year of experience in STEM, computer science, information systems, physics, mathematics, bio or statistics, computational chemistry, data science, machine learning, artificial intelligence or similar OR High School/ GED and at least 4 years of experience in STEM, computer science, information systems, physics, mathematics, bio or statistics, computational chemistry, data science, machine learning, artificial intelligence or similar.
• Basic level skill in at least one general purpose programming language, such as Python, PySpark, etc.
• At least 1 year of experience working with large-scale, complex datasets to create/optimize machine learning, predictive, forecasting, and/or optimization models.
• Basic level skill in SQL or any other relational and non-relational databases.
• Basic 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
• Willing to travel up to 10% of the time for business purposes (within state and out of state).

Preferred Qualifications

• 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 designing and analyzing A/B experiments.
• Basic 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, Numpy, Scikit-learn, Matplotlib, statsmodels, SciPy or similar frameworks.
• Basic level skill with any Cloud environment.
• Experience with Cloud ML platforms, distributed computing, data pipelines, cloud data stores is a plus.
• Experience with TensorFlow/PyTorch is a plus
• Experience in Healthcare is a plus.
• Experience with NLP
• Experience with non-relational databases
• Experience and knowledge of of distributed / parallel computing