Sr Analyst, Industry & Segment Analytics

Date Posted:

2024-11-14

Country:

United States of America

Location:

HAZ99: Field Office - AZ Remote Location, Remote City, AZ, 85001 USA

Position Role Type:

Remote

Are you a data analyst who is interested in strategy? The Sr Analyst, Industry and Segment Analytics is part of the Collins Aerospace Corporate Strategy organization. The Industry and Segment Analytics team is responsible for informing key decisions, crafting industry outlooks, developing platform model and regional forecasts, providing foundational data, defining key segment trends, distributing insightful analyses, educating future leaders, and serving as influential thought leaders.

 

The Corporate Strategy organization influences the long-term vision of Collins Aerospace by working with teams across the company focused on strategic planning and analysis, competitive intelligence, strategic forecast initiatives, critical decision support, mergers and acquisitions, portfolio analysis as well as revenue synergies. Other important stakeholders include Strategic Advisory Council (SAC), Finance, Investor Relations, Board of Directors, Customer Account Management, sales inventory operations planning (SIOP), and aftermarket teams.

 

This position can be worked remotely from anywhere in the domestic US.

 

What You Will Do:

• Analyze key industry trends and leading indicators within commercial aerospace to signal business impacts to Collins Aerospace

• Conduct complex forecast modeling to evaluate short and long-term scenarios to better understand size, growth and risk

• Leverage Tableau to manage existing and create new insightful internal and external visualization dashboards

• Develop and maintain scripts in Python and SQL using integrated development environments and relational database management systems like Jupyter, SSMS, PGAdmin, Visual Studio Code for automation, coding, debugging, and testing

• Develop and maintain ETL workflows that interact with a variety of systems

• Review aggregate data inputs, forecast-to-actuals, external analysis and perform deep-dives to improve business intelligence and forecasts

• Provide analyses, forecasts and insights in support of team peer processes relevant to commercial fleet forecasts, utilization, and airline health assessment

• Partner with strategic business units (SBUs) on future analytics projects and forecasting opportunities with internal and external data sets

• Create PowerPoint presentations that are used in consultation with segment leaders to provide recommendations and develop business strategies

• Provide training on key tools to various internal and external team members

• Perform ad hoc requests from management and executive leadership

• Present key findings to leadership in a clear and concise manner

• Travel expectations <10% (Domestic 1-2 weeks a year)

 

What You Will Learn:

• You will gain exposure and contribute to company and product strategy development.

• You will learn all aspects of commercial aerospace industry dynamics, players, trends, and drivers.

• You will become a subject matter expert in commercial aerospace traffic, capacity, and load factors.

 

Qualifications You Must Have:

• Typically requires a University Degree and minimum 2 years of prior relevant experience or an Advanced Degree in a related field or in absence of a degree, 6 years of relevant experience.

• Must be authorized to work in the U.S. without sponsorship now or in the future. Collins Aerospace will not offer sponsorship for this position.

• 2+ years of experience in a data focused role, including designing, implementing, and optimizing data pipelines and Extract, Transform & Load (ETL) processes.

 

Qualifications We Prefer:

• Experience with MS Office, SQL, Alteryx, and Tableau

• Programming skills in Python and proficiency with libraries and frameworks such as Pandas, Selenium, and SQL Alchemy

• Experience working with relational databases with an emphasis on creating and maintaining database tables and views

• Experience working with large-scale datasets,