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 structured and semi-structured data using SQL.
• Optimization and Modeling Skills: Strong understanding of optimization techniques and financial modeling; background in A/B testing, hypothesis testing, causal analysis, and predictive modeling is a plus.
• Analytical and Problem-Solving Skills: Capacity to translate complex business problems into actionable insights using rigorous analytical techniques.
• Collaborative Mindset: A team player with a growth-oriented attitude, strong prioritization skills, and a commitment to continuous learning.

Outcomes:

• Deliver insights that drive measurable improvements in revenue growth, cost management, and operational performance.
• Develop a robust understanding of the data ecosystem, identifying opportunities for improved governance, infrastructure, and process automation.
• Champion a culture of data-driven decision-making by demonstrating the value of advanced analytics techniques and supporting stakeholders in leveraging tools like Looker, SQL, and Python.