Senior Director of Data Science and Analytics

Overview

Atlas Air is looking for an exceptional Senior Director of Data Science & Analytics to lead our data-driven transformation and unlock actionable insights that will drive business growth, operational excellence, and fuel Atlas Air’s competitive advantage in the outsourced aviation industry. This role will be instrumental in building and scaling our data science and analytics capabilities while directly contributing to our value creation initiatives across our company.

Reporting to the VP of Data & Analytics, you will lead a team of data scientists, analysts, and engineers to deliver sophisticated analytics solutions that informs strategic decision-making, optimize operations, and identify new revenue opportunities. This is a high-impact leadership role for someone who thrives in a fast-paced, results-oriented environment where data drives every major business decision. We are looking for an enthusiastic, hands-on, get-it-done, team-driven leader with experience in building and delivering high-impact solutions that drive measurable business outcomes.

The Senior Director of Data Science and Analytics will partner with senior stakeholders across the company to help teams draw insights from their data. This individual will play a key role in helping lead the transformation of Atlas Air into a data driven and innovative leader in the transportation and logistics industry. As one of the company’s key data evangelists, you will help embed a data-driven culture across the company. You will help define the vision for our data science and analytics strategy, while leading a team of talented machine learning engineers, data scientists, and data analysts to implement that vision.

Responsibilities

• Partner with executive leadership to identify high-impact data use cases that drive measurable business outcomes.
• Define and execute the comprehensive data science, machine learning and analytics strategic roadmap aligned with business objectives and value creation goals.
• Build data science capabilities from the ground up, establishing best practices, methodologies, and governance frameworks.
• Recruit, develop, and retain top-tier data science and analytics talent.
• Lead and mentor a team of data scientists, machine learning engineers, and data analysts, fostering innovation, growth, and technical excellence.
• Build a high-performing, collaborative team culture focused on innovation and continuous learning.
• Manage project prioritization, resource allocation, and budget for the data science and analytics function.
• Drive the development of advanced analytics, machine learning, and AI solutions to solve complex business problems.
• Develop and track key performance indicators to measure the impact of data initiatives.
• Build and maintain strong relationships with key stakeholders across the organization.
• Outstanding communication skills with ability to present complex technical concepts to non-technical stakeholders.
• Proven ability to influence and drive change across organizations.
• Present insights and recommendations to executive and senior stakeholders.

Qualifications

• Advanced degree (MS/PhD) in Computer Science, Data Science, Statistics, Mathematics, Economics, or related quantitative field.
• 12+ years of progressive experience in data science and analytics, with at least 5 years in leadership roles.
• Demonstrated success in translating complex analytical insights into actionable business strategies.
• Proven track record of building and scaling data science teams in high-growth environments.
• Deep expertise in machine learning, statistical modeling, experimental design, and causal inference.
• Strong proficiency in Python, R, SQL, and modern data science tools and frameworks.
• Strong knowledge of modern data stack technologies (e.g., Snowflake, Databricks, Airflow, dbt, etc.).
• Experience with cloud platforms (AWS, GCP, Azure) and big data technologies (Spark, Hadoop, etc.).
• Outstanding communication and interpersonal skills with the ability to influence at all levels.

Preferred Experience

• Exceptional leadership and people management capabilities with experience building teams from 10-50+ people.
• Background in scaling analytics capabilities across multiple business units or companies.
• Experience with real-time analytics, recommendation systems, or customer analytics.
• Previous experience in relevant industry verticals (technology, aviation, transportation, and/or logistics).
• Background in machine learning operations (MLOps) and data science infrastructure.
• Track record of speaking at industry conferences or publications on data science, or machine learning topics.