SFO aims to optimize the guest experience at the airport, reduce operational costs, and increase revenue through the integration of video analytics, structured/unstructured data, and AI/ML capabilities.
Requirements
- Five (5) years of experience with probability and statistics, including experimental design, predictive modeling, optimization, and causal inference.
- Experience with machine learning concepts: regression and classification, clustering, feature selection, curse of dimensionality, bias-variance tradeoff, neural networks, SVMs, etc.
- Knowledge in time-series analysis.
- Familiarity with scripting language and/or shell scripting.
- Software development life-cycle experience, with proven track record of shipping products.
- Experience with big data and distributed system technologies like Hadoop, Mongo, Couch, Spark.
- Knowledge of both SQL and NoSQL databases.
Responsibilities
- Define the roadmap for integrating video analytics, structured and unstructured data, and Artificial Intelligence/Machine Learning (AI/ML) capabilities into business strategies.
- Identify opportunities to leverage video data for insights, automation, and innovation.
- Lead the development of solutions for extracting insights from video, structured and unstructured data.
- Research, prototype, and deploy advanced AI/ML models for structured (3rd Party applications, APIs, streaming data) and unstructured data (video/audio/other). Oversee model lifecycle management, from design to deployment and monitoring; ensure scalability, performance, and accuracy of AI/ML solutions.
- Work closely with Data Engineers, Architects and CI/CD Engineers to design data pipelines that handle structured and/or unstructured data efficiently. Implement real-time and batch processing capabilities for data streams. Proficiency in DataOps or MLOps methodologies and processes for integration and automation in cloud environments.
- Lead a team of data scientists, machine learning engineers, to provide mentorship and foster innovation. Collaborate with stakeholders across departments to understand requirements and translate them into technical solutions.
- Develop metrics and KPIs to evaluate the performance of video analytics systems. Implement continuous improvement strategies by iterating on models and algorithms.
Other
- An associate degree in computer science or a closely related field from an accredited college or university OR its equivalent in terms of total course credits/units.
- Bachelor’s or Master’s degree in applied mathematics, statistics, computer science, physics, engineering, or other relevant technical field.
- Knowledge AWS Sagemaker, Azure ML, GCP Vertex AI, or Snowflake Cortex.
- Knowledge of Cloud Data Warehouses like Snowflake, Big query, Redshift, Databricks etc.
- Experience in Java, Pig, Python, or Scala.
