Director leading agentic AI and machine learning products for Instacart’s grocery technology platform. Building retailer solutions and guiding teams from strategy through production deployment.
About the role
- Machine Learning Specialist developing AI, models, and analytical data products for the Government of Alberta. Applying machine learning to improve public services and policymaking.
Responsibilities
- Provide hands-on support, leadership, advice, and direction on strategic data initiatives
- Coordinate with internal and external clients to understand analytics needs and determine how data can best meet them
- Create tools, models, and analyses applying artificial intelligence to improve government policy and services
- Work with cross-functional project teams to apply machine learning
- Help teams identify when and when not to apply machine learning, including prerequisites for effective applications
- Facilitate, coach, and mentor others in applying machine learning to complex public challenges
- Help identify and select machine-learning tools, services, and infrastructure
- Create data collection, normalization, and cleaning procedures
- Create training scripts and train models for specific domains using selected machine-learning packages
- Run machine-learning-driven analyses of large datasets and report findings
- Create ML analytics, reports, and insights to inform better services and policymaking
- Integrate trained ML models within applications
- Develop auditing, accountability, and transparency mechanisms for ML capabilities
- Work within privacy legislation and provide ethical and practical guidance on ML implementation
- Develop and share analytical models and products
- Analyze and organize raw data for prescriptive and predictive modeling and build algorithms delivering business value
- Support development of full-stack data analytics or AI applications as required
- Provide expertise and leadership in the design and completion of analytic projects
- Conduct complex data analysis and collaborate with data engineers and analysts
- Gather and document client requirements
- Capture business and technical metadata for ML products
- Escalate issues and risks as appropriate
- Work within a multi-vendor/staff environment
- Perform other responsibilities as required or requested
Requirements
- Expertise in machine learning and a diverse range of analytical skills
- Experience in machine-learning model development, artificial intelligence, data analysis, data science, AI development, data engineering, data modelling, or statistical analysis
- Knowledge of data architecture, technical analysis, business analysis, and data product design and delivery
- Ability to apply machine learning to complex public challenges
- Knowledge of ML tools, services, infrastructure, and packages
- Ability to create data collection, normalization, and cleaning procedures
- Ability to create training scripts and train domain-specific models
- Experience running ML-driven analyses of large datasets
- Ability to integrate trained ML models within applications
- Knowledge of auditing, accountability, and transparency mechanisms for ML capabilities
- Ability to work within privacy legislation and provide ethical guidance on ML implementation
- Skills in prescriptive and predictive modelling and algorithm development
- Experience with full-stack data analytics or AI applications
- Knowledge of statistical classification techniques including k-means clustering, hierarchical clustering, partition trees, and logistic regression
- Ability to gather and document client requirements
- Ability to capture business and technical metadata for ML products
- Ability to work in a multi-vendor/staff environment
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Degree requirement
No Education Requirement
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