What are the responsibilities and job description for the Senior Data Scientist - Optimization & Automation position at Airspace?
Overview:
The Data & Analytics team at Airspace delivers impactful insights and builds intelligent solutions that drive our product and business strategies. We are seeking a results-oriented individual with expertise in Python, optimization, statistical analysis, and automation to solve complex problems in time-critical logistics. This role is tailored for a technical and quantitative expert who thrives on creating end-to-end solutions, from identifying business challenges to deploying scalable, automated models and tools.
What You Will Do:
- Optimization Models for Logistics Operations: Collaborate with product and engineering teams to design and implement optimization models for logistics, focusing on dynamic pricing, route efficiency, resource allocation, and other complex challenges.
- Automation and API Integrations: Build automated pipelines to streamline data workflows, integrating with external APIs (e.g., logistics, pricing, and financial systems) using technologies like Python and GCP Cloud Functions.
- Cross-Functional Collaboration: Partner with product, revenue, operations and finance teams to align data science initiatives with business objectives, translating requirements into robust, data-driven solutions.
- 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 pricing strategies, budgeting, and cost forecasting, helping to drive data-informed decision-making.
- Advanced Statistical Analysis: Conduct rigorous statistical analyses, including A/B testing, hypothesis testing, causal impact modeling, and predictive analytics, to validate experiments and inform strategic decisions.
What You Will Bring:
- Experience: Minimum 4 years in data science or related field, with a strong focus on Python programming, automation, API integrations, and statistical analysis. A Masters degree or PhD in data science, computer science, or related quantitative field is desirable.
- Python Proficiency: Expertise in Python, with a focus on building scalable data pipelines, automation scripts, and API integrations.
- SQL and Data Manipulation Skills: Advanced knowledge of SQL for working with structured and semi-structured data.
- Optimization Expertise: Deep understanding of optimization techniques, including linear programming, mixed-integer programming, and heuristics. Experience in solving operational or logistics-related problems is highly valued.
- Statistical and Analytical Skills: Advanced understanding of statistical methods, experimental design, and causal inference.
- Problem-Solving Mindset: Demonstrated ability to break down complex problems, identify root causes, and design scalable, data-driven solutions.
- Team Collaboration: Strong communication and collaboration skills with an ability to work cross-functionally and influence technical and non-technical stakeholders.
Outcomes:
- Deliver advanced optimization and predictive models that drive measurable improvements in operational efficiency and cost reduction.
- Automate key processes across the analytics stack to improve efficiency and scalability.
- Enable stakeholders to make data-driven decisions by developing tools, dashboards, and insights that simplify complex data.
- Contribute to a culture of innovation by introducing advanced data science techniques and mentoring team members.
Compensation:
- Competitive total salary: $140k - $180k
- 401K program, high-quality health, and dental care plan options
- lunches, onsite gym, and more
Salary : $140,000 - $180,000
