Lead Engineer - Analytics, Engineering Data Science Lab

GE Aviation
Date Posted: 
September 22, 2019
[email protected]

The ideal candidate for Lead Engineer - Analytics, Engineering Data Science Lab will lead all digital aspects of Engineering division process initiatives. He/she will help identify, drive, and execute strategic process Initiatives aligned to the organizational blueprint. This role will be responsible for developing a culture of process innovation connecting our business digitally through data, quality transformation, and process excellence. The expectation is this person becomes a leader for digital transformation within the division and the business with focus on advanced analytics, AI and machine learning capabilities.


- Lead & influence division and cross-division initiatives focused on processes that impact the organization and overall cash to the business
- Partner with Business Leaders and stakeholders to determine critical process initiatives and targets for key processes. Initiate and ensure successful execution on projects, applying simplification/quality tools to ensure proper rigor & drive process effectiveness & improvements
- Provide leadership, facilitation, training, and in-depth expertise on process innovation tools and data driven methodologies (Fastworks, Lean Six Sigma, Digital Analytics, Data Science, CAP- Change Acceleration Process)
- Work cross-functionally and cross-division to leverage best practices and maximize desired outcomes for the business and our customers
- Help develop communication plans and proactively communicate priorities, progress, status and issues to relevant champions (EB/SEB-level Leaders) in a clear and succinct way
- Proven leadership capabilities with ability to motivate others and achieve results within a highly technical environment


- Knowledge of digital tools, data science, and machine learning
- Familiar in programming with one or more languages (Python, R, Java, C, C++)
- Demonstrated ability to work together with large development solution team involving skills from client-server architecture, Java/Springboot /Hadoop/Spark/Hive/Postgres/Docker
- Experience developing machine learning capabilities – such as deep learning, anomaly Detection, Bayesian Probabilistic Methods, and Deterministic hybrid Methods, etc.
- Engineering domain expertise in Aerospace engineering, Mechanical design, Manufacturing, Supply-chain, etc.
- Strong analytical and quantitative skills
- Strong verbal and written communication skills, can articulate succinctly to all levels of the organization. Proven team player and demonstrated ability to work horizontally
- Proven time management & organizational skills; demonstrated ability to prioritize, multi-task, and perform in a time pressured environment


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