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Senior Director Data Products

Atlas Air, Inc
Miami, FL Other
POSTED ON 10/20/2024 CLOSED ON 4/26/2025

What are the responsibilities and job description for the Senior Director Data Products position at Atlas Air, Inc?

Overview

The Senior Director of Data Products, will partner with senior stakeholders across the airline to help teams draw insights from their data and visualize performance goals. As one of the company’s key data evangelists, you will help embed a data-driven culture across the company. You will build a team who can realize value from the company’s many data sources by introducing data products ranging from dashboards to advanced machine learning models. Your thought leadership in innovative data techniques and ability to apply deep aviation-industry experience will allow you to create value across commercial, operational and other domains.

Responsibilities

  • Support the VP, Data & Analytics in constructing an enterprise data strategy and roadmap.
  • Inspire and evangelize advanced analytics, and help Atlas Air understand the emerging technology available in the domain of data science such as AI and Machine Learning.
  • Lead a team of 15-20 people and accountable for reporting, analytics and data science across the company’s diverse set of domains and use cases.
  • Recruit and motivate an effective data realization team and grow this new function and team as required in the coming years.
  • Lead the development of innovative data products and services that improve company performance. This ranges from crew repair, disruption management to supply chain optimization and crew resource forecasting.
  • Assess the current data assets at Atlas and work closely with the analytics engineering team to define the data schemas needed to build out the core data for the future.
  • Oversee the team responsible for these core data models as well as documentation, training, and delivery to departments in preferred formats.
  • Hands-on leadership and coaching of team members working on BI, performance reporting, data science, and work closely with data architecture, data platforms, infrastructure, and data governance team members.
  • Help build business cases cost/benefit/risk analysis for new initiatives and projects.
  • Help foster an overall IT team culture of speed-to-value and accountability. 

Qualifications

  • College degree in data science, computer engineering, or similar field required.
  • Mature leader who excels in influencing senior leadership without direct authority. Understand how to build partnerships that cut across the organization, working closely with all levels and functions.
  • A minimum five years aviation experience and deep understanding of how an airline works and the underlying data needs that airlines have.  
  • A minimum of 12 years of experience building and leading data and analytics teams within the logistics, aviation or similar industry.
  • Extensive experience in working with stakeholders to identify business problems that can be solved with data and analytics. Proven track-record in building business cases to support investment in IT resources.
  • Has supervised gradual deployment of data science products with measurable impact and delivered significant bottom-line results. Ideal candidate will have done this within an airline of size.
  • Has experience in a business-facing data consultancy role with demonstrated ability to foster engagement and creativity across a large function or business unit.
  • Has ability to provide hands-on coaching and mentoring for a data team, i.e. has experience designing database models, running data analysis projects as well as building reports and dashboards.
  • Has experience leading teams and building consensus around data requirements. Must have experience recruiting teams from the ground up and establishing data governance across a large scope.  
  • Has worked directly with data/analytics engineers and data architects in defining schemas and building cloud data platforms. Ideally has a good working understanding of modern data warehouses (e.g., Snowflake, Databricks, BigQuery) and modern analytics engineering (e.g., using dbt).
  • Has a get it done attitude. Self-directed and functions well within ambiguity.
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