Experienced Data Scientist

Boeing•Hialeah, FL

About The Position

Experienced Data Scientist Company: Boeing Distribution, Inc. Boeing Global Services, Distribution Business, is looking for an Experienced Data Scientist to join our team in Hialeah, FL. The Senior Data Scientist will operate in a lead role, developing and building next generation Artificial Intelligence (AI) and Machine Learning (ML) products and services. This position will work effectively with cross-functional teams and technical leads to determining, defining, and deploying analytics solutions to meet business goals. At Boeing, we are already making a difference across the industry using AI and ML to deliver superior product experience to our internal functions and commercial and government customers. We are expanding and growing in all areas in the frontier of the aerospace industry. We already have some of the best minds and talents in this field, and we’re looking for someone with applied experience in AI and ML (including Natural Language Processing, Deep Learning, Conversational AI, and Computer Vision) to join our team in this senior data scientist role. Position Responsibilities: Evaluate business objectives, determine stakeholder needs, and identify requirements Choose best fit methods, define algorithms, validate, and deploy models to achieve business results Perform necessary data preparation and enhancements to models Interface directly with senior business leaders and stakeholders to architect and lead the development of advanced analytics solutions supporting Aircraft operations, Engineering, Manufacturing, Quality, and Safety Working with data scientists leads across domains to ensure functional excellence in this technical field and will provide mentoring, technical leadership, and training to the data scientist community to accelerate and develop this talent base Provide thought leadership for machine learning and advanced analytics methods at Boeing and externally Engage with stakeholders across the business to identify applications across the enterprise, beyond the initial use case, and lead the implementation of these applications to capture business value Evaluate technologies, assist in identifying capabilities gaps, develop and teach best practices and technology standards, and work alongside the rest of the global data scientists and technical leads in Analytics organization Ensure analytics solutions meet the business requirements and are implemented in a timely manner to validate business value Work effectively with cross-functional teams in the analysis of highly complex data sets using advanced analytics techniques such as machine learning, advanced statistical analysis, visual analysis, text analysis, mathematical optimization, and simulation Identify modeling attributes and parameters Follow best practices and standard processes for model validation and refinement as per business requirements Assess performance of models and analysis and confirm that business objectives were met Work with business unit stakeholders to develop and sustain analytics solutions

Requirements

5+ years of experience working with projects, teams, and/or leaders in the analytics and/or data science space
5+ years of experience researching and applying large language and generative AI models
5+ years of experience with various machine learning methods such as regression, clustering, classification, decision trees, natural language processing, ensemble methods, support vector machines (SVM), deep learning, reinforcement learning, etc.
5+ years of experience in designing and implementing Natural Language Processing (NLP) models using machine learning techniques including neural networks, deep learning and transformer architectures

Nice To Haves

Bachelor's degree or equivalent work or military experience
Master’s degree in data science or equivalent
Experience in supply chain domain
Experience in agile and product-oriented development
Experience in building ML models and bring into full production use within the industry
Experience training machine learning models in a cloud computing environment such as: Amazon Web Services, Google Cloud Platform, Microsoft Azure, etc.
Experience programming in one or more of the following: C, C++, Java, Python, Scala
Experience with statistical software (e.g., R, MATLAB) and database languages (e.g., SQL)
Experience with SAP (ERP)
Experience in advanced statistics (e.g., probability theory and distributions, descriptive statistics, matrix algebra, multivariate statistics, polynomial analysis, parametric and non-parametric methods, etc.)

Responsibilities

Evaluate business objectives, determine stakeholder needs, and identify requirements
Choose best fit methods, define algorithms, validate, and deploy models to achieve business results
Perform necessary data preparation and enhancements to models
Interface directly with senior business leaders and stakeholders to architect and lead the development of advanced analytics solutions supporting Aircraft operations, Engineering, Manufacturing, Quality, and Safety
Working with data scientists leads across domains to ensure functional excellence in this technical field and will provide mentoring, technical leadership, and training to the data scientist community to accelerate and develop this talent base
Provide thought leadership for machine learning and advanced analytics methods at Boeing and externally
Engage with stakeholders across the business to identify applications across the enterprise, beyond the initial use case, and lead the implementation of these applications to capture business value
Evaluate technologies, assist in identifying capabilities gaps, develop and teach best practices and technology standards, and work alongside the rest of the global data scientists and technical leads in Analytics organization
Ensure analytics solutions meet the business requirements and are implemented in a timely manner to validate business value
Work effectively with cross-functional teams in the analysis of highly complex data sets using advanced analytics techniques such as machine learning, advanced statistical analysis, visual analysis, text analysis, mathematical optimization, and simulation
Identify modeling attributes and parameters
Follow best practices and standard processes for model validation and refinement as per business requirements
Assess performance of models and analysis and confirm that business objectives were met
Work with business unit stakeholders to develop and sustain analytics solutions