Machine Learning Specialist

This is a fully remote position, open to applicants in Canada.

📋 Description

• Deliver practical support, leadership, counsel, and guidance on strategic data initiatives.

• Collaborate with both internal and external clients to identify analytics requirements and determine how data can optimally address them.

• Develop tools, models, and analyses that utilize artificial intelligence to enhance government policies and services.

• Partner with cross-functional project teams to implement machine learning solutions.

• Assist teams in recognizing when to apply machine learning and the necessary prerequisites for effective usage.

• Facilitate, coach, and mentor colleagues in the application of machine learning to tackle complex public issues.

• Aid in the identification and selection of machine-learning tools, services, and infrastructure.

• Establish procedures for data collection, normalization, and cleaning.

• Produce training scripts and train models tailored for specific domains utilizing selected machine-learning packages.

• Execute machine-learning-driven analyses on large datasets and present findings.

• Generate ML analytics, reports, and insights to enhance service delivery and policymaking.

• Incorporate trained ML models into applications.

• Create auditing, accountability, and transparency mechanisms for ML functionalities.

• Operate within privacy regulations and provide ethical and practical advice on ML execution.

• Develop and disseminate analytical models and products.

• Analyze and organize raw data for prescriptive and predictive modeling while constructing algorithms that deliver business value.

• Support the development of full-stack data analytics or AI applications as necessary.

• Offer expertise and leadership in the design and execution of analytic projects.

• Conduct sophisticated data analyses and collaborate with data engineers and analysts.

• Collect and document client requirements.

• Capture business and technical metadata for ML products.

• Identify and escalate issues and risks as needed.

• Function effectively in a multi-vendor/staff environment.

• Undertake additional responsibilities as required or requested.

⛳️ Requirements

• Proficiency in machine learning along with a diverse set of analytical skills.

• Experience in developing machine-learning models, artificial intelligence, data analysis, data science, AI development, data engineering, data modeling, or statistical analysis.

• Understanding of data architecture, technical analysis, business analysis, and the design and delivery of data products.

• Capability to apply machine learning to intricate public challenges.

• Familiarity with ML tools, services, infrastructure, and packages.

• Competence in creating procedures for data collection, normalization, and cleaning.

• Ability to develop training scripts and train models specific to certain domains.

• Experience in conducting ML-driven analyses on large datasets.

• Skill in integrating trained ML models into applications.

• Knowledge of auditing, accountability, and transparency mechanisms related to ML capabilities.

• Ability to navigate privacy legislation and provide ethical guidance on ML implementation.

• Proficiency in prescriptive and predictive modeling as well as algorithm development.

• Experience with full-stack data analytics or AI applications.

• Understanding of statistical classification techniques such as k-means clustering, hierarchical clustering, partition trees, and logistic regression.

• Ability to gather and document client requirements.

• Competence in capturing business and technical metadata for ML products.

• Ability to thrive in a multi-vendor/staff environment.

🏝️ Benefits

• Comprehensive benefits package.

• Opportunities for professional development and growth.

• Collaborative work environment with a focus on innovation.

• Flexible work arrangements.