Data Science Specialist

Job Description Summary

The Data Science Specialist will develop and implement Artificial Intelligence based solutions across various disciplines in GE Aerospace under the guidance of senior team members. In this role, the candidate will contribute to the development and deployment of modern machine learning, artificial intelligence, statistical methods, operations research, semantic analysis etc. for finding structure in large data sets.

Job Description

Essential Responsibilities:

The Data Scientist will be responsible to work on data science projects under the supervision of senior team members and deliver business outcomes. Key responsibilities include -

• Development of data science models.
• Work alongside software developers and software engineers to translate algorithms into viable products and services.
• Work in technical teams in development, deployment, and application of applied analytics, predictive analytics, and prescriptive analytics.
• Perform exploratory and targeted data analysis using descriptive statistics and other methods.
• Work with data engineers on data quality assessment, data cleansing and data analytics.
• Generate reports, annotated code, and other projects artifacts to document, archive, and communicate the work and outcomes.
• Share and discuss findings with team members.

• Masters or PhD degree in Statistics, Machine Learning, Computer Science or related field
• Proficiency in Python (mandatory).
• Demonstrated skill at data cleansing, data quality assessment, and using analytics for solving business problems
• Demonstrated skill in the use of applied analytics, descriptive statistics, feature extraction and predictive analytics on datasets
• Demonstrated skill at data visualization and storytelling for an audience of stakeholders
• Strong communication and interpersonal skills

• Influences within peer group.
• Implements specific component(s) of the roadmap.
• Evaluates features using well known or prescribed recipes and appropriately down selects to valuable ones.
• Aware of models such as CART / SVM / RF / Neural Net and the associated sub-models
• Uses Cross Validation and other Verification & Validation techniques to build robust models from large data sets.
• Understands the types of issues that impact data quality
• Performs basic data cleaning operations such as flagging missing and invalid data etc.
• Fits normal parameters to data and assess goodness of fit
• Can use and interpret t-tests, ANOVA and basic hypothesis testing with good utilization of p-values.
• Codes using modular practices for reusage and object-oriented Effectively shows visualization of data exploration using box, bubble and matrix plots.
• Has a basic understanding of GE Aerospace business and how the tools they are developing create value.
• Humble: respectful, receptive, agile, eager to learn
• Transparent: shares critical information, speaks with candor, contributes constructively
• Focused: quick learner, strategically prioritizes work, committed
• Leadership ability: strong communicator, decision-maker, collaborative
• Problem solver: analytical-minded, challenges existing processes, critical thinker