Duration: 12 months to start
Job Description:
Summary:
The organization is looking for an experienced data scientist who can play lead role in developing and building next generation AI & ML products and services. This position will work effectively with cross-functional teams and technical leads to determine, define, and deploy analytics solutions to meet business goals. We are already making a difference across the industry using AI and Machine Learning 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 talent in this field, and we’re looking for someone with applied experience in AI and ML (including Natural Language Processing, Deep Learning, Conversational A.I, and Computer Vision) to join our team in this lead 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.
- Candidate will 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.
- Candidate will work with data scientist 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. In particular, candidate will provide thought leadership for machine learning and advanced analytics methods at Boeing and externally.
- Candidate will actively 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.
- Candidate will 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.
- Candidate will have a stake in ensuring analytics solutions meet the business requirements and are implemented in a timely manner to validate business value.
- ML/AI Models Development:
- 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.
Required Qualifications (Required Skills & Experience):
- A Master's degree in data science or equivalent field.
- A Bachelor's degree in a quantitative/technical field (e.g. science, economics, quantitative finance, operations research, statistics, mathematics, or similar information technology field of study).
- 7+ years of relevant work experience as Data Scientist in core areas of Machine Learning, NLP, GenAI, Agentic AI, computer vision & image processing.
- Experience in various machine learning method such as regression, clustering, classification, decision trees, natural language processing, ensemble methods, SVM, deep learning, reinforcement learning, etc.
- Experience with machine learning related open source libraries including, but not limited to: SciKit-Learn, Keras, TensorFlow, Theano, etc.
Preferred Qualifications (Desired Skills/Experience):
- Experience in supply chain domain
- Experience in agile and product-oriented development.
- Up-to-date industry and experience in building ML models and bring in to full production use.
- Background in developing customer-facing experiences, a strong technical ability, excellent project management skills, great communication skills, and a motivation to achieve results in a fast paced production environment
- Experience training machine learning models in a cloud computing environment such as: Amazon Web Services, Google Cloud Platform, Microsoft Azure, etc.
- Programming experience 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).
- Strong team player and passion to execute projects with a focus on customer and value.
- Knowledge of advance statistics (probability theory and distributions, descriptive statistics, matrix algebra, multivariate statistics, polynomial analysis, parametric and non-parametric methods, etc.)
