DescriptionThis Senior Manager will add quantitative sophistication to business decisions by turning data into information and information into insight. This person will also partner with business owners to pursue analytical opportunities within maintenance planning, supply chain, aircraft health monitoring, aircraft engineering, maintenance execution, and maintenance programs, among other areas. Additionally, this person will demonstrate analytical aptitude while scoping strategic projects that link business problems and quantitative methods. This role also leads the Standards and Excellence analytics capability and the performance governance system behind it - KPI design, dashboard and data product roadmaps, and benefits realization routines - partnering with Digital Technology, Process Standards, Continuous Process Improvement, Projects & Execution and Change Management so insight translates into measurable operational and financial results.
- Manager a team of 3-4 data analysts by guiding them on modeling techniques, approaches, and methodologies
- Parter with business teams throughout Technical Operations and United to uncover previously unknown opportunities that can be solved quantitatively; define use cases and manage the analytics portfolio based on value, complexity, and business need
- Ensure alignment and prioritization with business objectives and initiatives - help business owners make faster, smarter decisions; translate the Standards and Excellence strategy into the analytics strategy, metric architecture, and dashboard and data product roadmap
- Design KPIs and objective functions to unify disparate business units, aligning goals and incentives; establish and maintain KPI governance, metric definitions, data quality controls, review cadences, ownership routines, and sustainment mechanisms so analytics products remain trusted, actionable, and embedded in ongoing business performance management
- Build and deliver presentations that explain drivers of operational performance, including recommendations on how to improve outcomes; translate complex analysis into executive-ready stories, recommendations, and decisions
- Execute solutions to business problems using data analysis, data mining, optimization, statistical modeling, and machine learning techniques; identify trends, root causes, and constraints in operational and financial data
- Translate analytical models directly into business actions while keeping in mind constraints of existing systems and processes; partner with Digital Technology, and platform teams to design, build, and activate data assets, dashboards, and decision-support tools, connecting delivered work to measurable operational and financial outcomes
- Encourage development and sharing of internal best practices and foster collaboration with internal and external teams
NOTE: This position is located at the CSC-Willis Tower in Chicago, IL and considered as a hybrid role working 3 days in office, however that may evolve with the needs of the company.
QualificationsWhat's needed to succeed (Minimum Qualifications):- Bachelor's degree in a quantitative field such as Mathematics, Statistics, Operations Research, Economics, Computer Science, Engineering or related work experience
- 5+ years of experience in data science and/or analytics
- 2+ years of experience in a leadership/supervisory role
- Experience with the following multiple areas: exploratory data analyses, feature engineering, clustering, regressions, tree methods, supervised and unsupervised learning, reinforcement learning, neural networks, natural language processing, simulation, optimization, and other parametric and nonparametric classification methods
- Expertise in at least one quantitative analysis package - i.e. Python, R, etc.
- Proficiency in writing complex queries and procedures using SQL
- Data visualization skills using one or more reporting tools - i.e. Spotfire, Tableau, ggplot2, etc.
- Deep technical knowledge of statistics and machine learning methods, including testing model assumptions, and selecting the most appropriate methods
- Aptitude communicating complex quantitative analysis and algorithms in a clear, precise, and actionable manner (non-technical and technical, all levels of management
- Strong relationship management and influence skills across business, technical, and operational stakeholders
- Business development skill to source new analytics projects, apply team's analytics capabilities to business problems, and build relationships with stakeholders to assist with operational decision-making
- Experience taking projects from the exploratory phase to completion by learning a business problem, finding the data required, building models from scratch, and deploying a solution to end users
- Demonstrates an understanding of the capabilities and limitations of generative AI tools and effectively leverage them to support research, analysis, content creation, and problem-solving. Applies critical thinking to validate AI-generated outputs while adhering to organizational policies for responsible AI use, data privacy and security
- Must be willing and able to travel 5-10%
- Must be willing and able to work a hybrid work schedule, 3 days in office (Tue-Thu) at the CSC-Willis Tower in Chicago, IL
- Must be legally authorized to work in the United States for any employer without sponsorship
- Successful completion of interview required to meet job qualification
- Reliable, punctual attendance is an essential function of the position
What will help you propel from the pack (Preferred Qualifications):- Master's degree in a quantitative field like Math, Statistics, Operations Research, Economics, Computer Science, Engineering and/or MBA or related work experience
- 7+ years of experience in analytics
- Airline experience or knowledge of airline operations
- Familiarity with aircraft systems and/or maintenance
- Experience with predictive maintenance, reliability analytics, operational performance management, or labor productivity analysis
- Lean Six Sigma Certification
- Understanding of experimental design principles
- Background with cloud computing and big data platforms - particularly PySpark and/or Hadoop, Databricks, Palantir or similar ecosystems
