Maintenance Forecasting Analyst

Location

US-CT-EAST HARTFORD-ETC ~ 400 Main St ~ BLDG ETC

Military and commercial aviation industries are complex and increasingly data driven. Today's aircraft and engines have a multitude of sensors creating a myriad of data elements from which predictive inferences are made. We are in a unique position as the only group in Military Engines that has the expertise to distill massive datasets into actionable information to support mission critical operations.

We create predictive intelligence providing our customers with the ability to take meaningful action and make critical decisions enhancing mission readiness of our Nation and allies. Our analysts have the expertise to create custom analytical models based on specific customer requirements and needs, including agent-based simulation, hybrid discrete-continuous simulation and stochastic optimization in addition to standard à la carte options.

The primary focus for this candidate will be setting up and running state machine models to further efforts around forecasting and scenario analysis to assist with overhaul, repair and maintenance scheduling of military engines, including software development of mathematical models and implementing analysis and visualizations of results. Additionally, this role may assist with developing and implementing software state machine models, stochastic modeling, and at times may develop and maintain machine learning algorithms as necessary to enhance the current forecasting modeling software.

• Effectively manage priorities to produce timely and efficient delivery of forecasts to customers according to requirements and customer need, with high quality and without error.
• Deliver multiple scenario analyses for each forecast based upon customer requests and identify data, metrics and analytical requirements to solve business use cases provided by customers.
• Troubleshoot model outcomes to ensure quality and accuracy by making simple C++ enhancements to existing code.
• Development of C++ and Python code to support existing FloSimLX tools to create enhancements and automation within the current model using predictive mathematical data science principles up to and including AI and machine learning techniques.
• Development of a Python web application, FAR, including front end development, computational algorithms and data loading to support forecasting accuracy initiatives.

• A University Degree or equivalent experience and minimum 5+ years prior relevant experience, or an advanced degree in a related field and minimum 3+ years in engineering/other technical positions. Experience to include: working with technical and non-technical partners such as product and technical managers, strong communication skills, advocacy and support of continuous improvement methodology within our lean manufacturing operating system, proficiency in Microsoft Excel, intermediate knowledge of data visualization tools (PowerBI or similar), knowledge of Agile ceremony and process methodology (Lean Agile), intermediate knowledge of Python, intermediate knowledge of data science mathematical principles including statistics, basic understanding of Microsoft development products such as Visual Studio.
• The ability to obtain and maintain a U.S. government issued security clearance is required. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance.

• Advanced knowledge of Python and C++.
• Advanced knowledge in probability and statistics.
• Intermediate knowledge of distributed processing of large data sets.
• Basic knowledge of cloud computing environments either with Azure or Amazon, including use of data science or AI/ML tooling within these spaces.

• Onsite:
  Employees who are working in onsite roles will work primarily onsite. This includes all production and maintenance workers, as they are essential to the development of our engines.
• Candidates will learn more about role type and current site status throughout the recruiting process. For onsite and hybrid roles, commuting to and from the assigned site is the employee’s personal…