Inventory Control Tower Business Intelligence Engineer

About the role

This role designs, builds, and operates the data, models, and logic that power the Inventory Control Tower, with a direct focus on inventory management execution, leveraging emerging technologies, business intelligence and AI/machine learning.

Responsibilities

• Promotes learning in others by proactively providing and/or developing information, resources, advice, and expertise with coworkers and members; builds relationships with cross-functional/external stakeholders and customers.
• Completes work assignments autonomously and supports business-specific projects by applying expertise in subject area and business knowledge to generate creative solutions; encourages team members to adapt to and follow all procedures and policies.
• Develops detailed problem statements outlining hypotheses and their effect on target clients/customers by defining scope, objectives, outcome statements and metrics.
• Designs and develops data pipelines and automation for data acquisition and ingestion of raw data from multiple data sources and data formats by transforming, cleansing, and storing data for consumption by downstream processes; writing and optimizing diverse SQL queries; and demonstrating advanced knowledge of database fundamentals.
• Analyzes and investigates complex data sets and summarizes key characteristics by employing data visualization methods; and determining how best to manipulate data sources to discover patterns, spot anomalies, test hypotheses, and/or check assumptions.
• Selects, manipulates, and transforms data into features used in machine learning algorithms by leveraging techniques to conduct dimensionality reduction, feature importance, and feature selection.
• Trains statistical models by using algorithms and data mining techniques; testing models with various algorithms to assess the input dataset and related features; and applying techniques to prevent overfitting such as cross-validation.
• Deploys and maintains reliable and efficient models through production.
• Verifies model performance by demonstrating expertise in the practice of a variety of model validation techniques to assess and discriminate the goodness of model fit; and leveraging feedback and output to manage and strengthen model performance.
• Collaborates with internal and external stakeholders across domains to develop and deliver statistical driven outcomes by delivering insights and values from heterogeneous data to investigate complex problems for multiple use cases; driving informed decision-making; and presenting findings to both technical and non-technical audiences.

Requirements

• Minimum three (3) years experience working with Exploratory Data Analysis (EDA) and visualization methods.
• Minimum three (3) years machine learning and/or algorithmic experience.
• Minimum three (3) years statistical analysis and modeling experience.
• Minimum three (3) years programming experience.
• Minimum one (1) year experience in a leadership role with or without direct reports.
• Bachelor's degree in Mathematics, Statistics, Computer Science, Engineering, Economics, Public Health, or related field AND Minimum five (5) years experience in data science or a directly related field. Additional equivalent work experience in a directly related field may be substituted for the degree requirement. Advanced degrees may be substituted for the work experience requirements.
• One (1) year experience working with Kubernetes.
• One (1) year experience working with Docker.

Qualifications

• Health Care Industry
• Influencing Others
• Learning Agility
• Organizational Savvy
• Problem Solving
• Short- and Long-term Learning & Recall
• Teamwork
• Topic-Specific Communication
• Advanced Quantitative Data Modeling
• Algorithms
• Applied Data Analysis
• Data Ensemble Techniques
• Data Extraction
• Data Manipulation/Wrangling
• Data Visualization Tools
• Deep Learning/Neural Networks
• Design Thinking
• Feature Analysis/Engineering
• Machine Learning
• Microsoft Excel
• Model Optimization
• Open Source Languages & Tools
• Project Management
• Relational Database Management