Company Introduction:

Airspace is a tech-enabled freight forwarder that’s redefining how the world’s most critical packages are delivered. Headquartered in Carlsbad, California, Airspace has employees who are based around the world. Our European headquarters is in Amsterdam, The Netherlands.

As a recognized leader in AI and machine learning, our team leverages data and patented technology to coordinate logistics across a global network of drivers and airlines. Our goal is to deliver those packages that are truly mission-critical in a way that is faster, more transparent, more secure, and more accountable than ever before. The items we deliver range from organs for transplant, to parts for critical machinery including grounded aircraft and highly sensitive components such as semiconductors.  

Airspace has been rated one of America’s best Startup Employers, listed as one of CNBC’s Disruptor 50 companies, and featured as an Innovation and Disruption leader by CBS News. Airspace has the support of leading investors such as Telstra Ventures, HarbourVest Partners, Defy Partners, DBL Partners, and Scale Ventures. To date the company has raised more than $140m. 

The company is growing rapidly and serving more places around the world than ever before. We are looking for passionate, motivated individuals who want to make an IMPACT every day to help us execute on our mission of reshaping the world of time-critical logistics. 

Senior Analytics Engineer - Optimization & Automation

Overview:

The Analytics team at Airspace provides insights and intelligence that inform our product and business decisions. We are seeking a data-driven individual with a strong foundation in Python, automation, optimization, and statistical analysis to tackle complex challenges in time-critical logistics. This role is ideal for someone with a quantitative or technical background who excels in automation, working with external APIs, and advanced analytical techniques. You should be intellectually curious, results-oriented, and a technical problem solver than can identify business problems and build end-to-end solutions to address.

What You Will Do:

• Cross-Departmental Analytics and Insights: Collaborate with finance, product, and engineering teams to gather requirements and develop solutions that meet cross-functional goals. Use data mining, statistical analysis, and hypothesis testing to deliver actionable insights for financial modeling, cost optimization, and revenue impact. Present findings in accessible ways to support data-driven decision-making across teams.
• Automations and API Integrations: Develop automated solutions across the analytics stack, integrating with external APIs (e.g. logistics, pricing, financial) and creating scalable models and tools using technologies such as GCP Cloud Functions, custom Python scripts/apps, etc
• Optimization and Problem Solving: Work closely with product and engineering teams to develop optimization models for logistics operations, such as route efficiency, resource allocation, and dynamic pricing.
• KPI Definition and Tracking: Establish and track key product and business KPIs. Build models, reports, and automated insights to monitor key metrics, identify underlying drivers, and recommend actionable changes.
• Financial Modeling: Create and maintain financial models to support budgeting, cost forecasting, and pricing strategies, helping to drive data-informed decision-making.
• Advanced Statistical Analysis: Conduct A/B testing, hypothesis testing, causal impact analysis, and other statistical analyses to validate experiments and support strategic decisions.

What You Will Bring:

• Experience: Minimum 4+ years in data analytics, with a strong focus on Python programming, automation, API integrations, and statistical analysis.
• Advanced Python Skills: Proficiency in Python for data manipulation, workflow automation, and external API integrations.
• SQL Expertise: Ability to work with structu