Airspace
Senior Data Scientist - Optimization & Automation
Airspace, Carlsbad, California, United States, 92002
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
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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
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