Data Scientist - Customer Service

JOB SUMMARY:

Data Scientists support business growth by using business intelligence software, advanced data mining techniques, and statistical analysis methodology to automate complex processes, visualize large data sets, and generate new insights. Data scientists are highly analytical, technically skilled, and have a passion for sharing their insights to a broad audience.

The Data Scientist position within the Textron Aviation Aftermarket Analytics team in Customer Service is responsible for identifying, developing, and executing solutions that support strategic initiatives by generating actionable insights and recommendations based on the latest data science methodologies. This role will have a focus on forecasting aircraft maintenance to assist with annual operational planning, discounting strategy, creating long term maintenance agreements, and ensuring we keep our service centers full.

At Textron Aviation, we are building a community of Data & Analytics professionals with an emphasis on collaboration and cross functional support. You will have the opportunity to work closely with your peers throughout the organization toward a vision of data driven strategy.

JOB RESPONSIBILITIES:

• Build, optimize, and automate data models to support business reporting and ad-hoc analysis
• Advise leadership on analytical, data-driven approaches to solve challenges and identify opportunities
• Develop statistical and machine learning models to answer business questions and make predictions using R, Python, and other programming languages
• Experiment and explore new technologies to support business objectives
• Monitor data models for accuracy and performance and update as needed to maintain quality
• Develop best practices and document proven solutions
• Interface with other data professionals throughout the organization to embrace cross functional growth in analytics capabilities
• Provide guidance to data analysts to support expanding descriptive models into a predictive or prescriptive environment
• Conduct training on data literacy and data science capabilities to data consumers
• Gather and document analytics project requirements from business stakeholders, identifying opportunities to apply advanced analytic approaches
• Explore and understand the inner workings and market context of an aircraft OEM
• Preprocess data using feature selection and/or dimensionality reductions algorithms within a pure code environment.
• Solve regression and classification problems using established machine learning techniques
• Evaluate and optimize the performance of machine learning models through results-based training and testing

EDUCATION/ EXPERIENCE:

• Bachelor’s degree required in Applied Mathematics, Statistics, Data Science, Computer Science plus 2 years relevant technical experience or bachelor’s degree in other related field plus 4 years relevant technical experience
• Aviation experience preferred

QUALIFICATIONS:

• Strong written and verbal communication skills
• Experience with Microsoft Office including Excel and PowerPoint
• Practical application experience with one or more analytics packages such as SAS, R, SQL, Python (& associated libraries), or similar
• Experience working with relational databases, APIs, and ML production environments
• Advanced analytics skills, including statistical characterization of large sets, regression modeling, probability distribution fitting, stochastic simulation, and multivariate sensitivity analysis
• Ability to identify relevant metrics and explain technical information to a broad audience
• Desire and ability to learn and leverage new software, tools, and processes in a self-learning environment
• Demonstrated aptitude to clean and prepare data using techniques such as compression, binning, normalization/scaling, and 1-hot encoding within a pure code environment (Notebook or IDE)
• Advanced matrix, multidimensional array, and table operations in pure coding environment
• Demonstrated ability to preprocess data using feature selection and/or dimensionality reductions algorithms within a pure code environment. This may include decision tree analysis, boosting, or Principal Component Analysis
• Technical ability to solve regression and classification problems using established machine learning techniques including SVM, logistic regression, and clustering.
• Basic understand of time-series data analysis and prediction modeling (ARIMA, SARIMA, exponential smoothing) or otherwise
• Technical ability to evaluate (i.e., F1 Score, Confusion Matrices, RMSE, etc.) and optimize the performance (i.e., grid search, hyperparameter tuning) of machine learning models through results-based training and testing
• Basic understanding of Neural Networks with the ability to train a basic multi-layer perceptron in a pure code environment utilizing activation functions like ReLU, Sigmoid, etc.

The above statements are intended to describe the general nature and level of work being performed by employees assigned to this job. They are not intended to be an exhaustive list of all responsibilities, duties, and skills required of personnel so classified.