Machine Learning Specialist

Job Title: Machine Learning Specialist

Location: Canada, Remote

Seniority on the skill/s required on this requirement: Intermediate

Estimated Duration: 12 months with possible extension for another 6 months

Work authorization: Any (candidate must be authorized to work in Canada)

Job Summary

The Data Centre of Excellence requires a Machine Learning Specialist to support the design and development of analytical data products and services, enabling the client to better leverage its data assets in support of its broader data strategy. Working within a team, this individual will play a key role in high-quality data modeling, applying algorithms, de-identification, synthetic data creation, visualizations, and evidence development for use across departments and with external stakeholders. This role may span aspects of machine learning (ML) model development, artificial intelligence (AI), data analysis, data science, data engineering, data modeling, statistical analysis, strategizing, advising, and data product design and delivery with potential aspects of data architecture, technical analysis, and business analysis.

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 those needs.
• Create tools, models, and analysis to apply artificial intelligence for improved policy and services.
• Work with cross-functional project teams to apply machine learning.
• Help teams identify when (and when not) to apply ML, including prerequisites for effective ML applications.
• Facilitate, coach, and mentor others in applying ML to complex public sector challenges.
• Help identify and select ML tools, services, and infrastructure.
• Create data collection, normalization, and cleaning procedures.
• Create training scripts and train models for specific domains using chosen ML packages.
• Run ML-driven analyses of large datasets and report on 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, providing ethical and practical guidance on ML implementation.
• Develop and share analytical models and products.
• Analyze and organize raw data, preparing it for prescriptive and predictive modeling, while building algorithms that deliver 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 on various projects.
• Apply statistical classification techniques such as k-means and hierarchical clustering, partition trees, and logistic regression.
• 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.
• Prepare weekly and monthly status reports.
• Other responsibilities as required or requested.

Requirements

Education

Bachelor's degree in Computer Science or a related field of study (equivalencies will be considered).

Required Work Experience

• 6 years of experience and comprehensive skills using statistical and computer languages (e.g., R, Python, SQL).
• 6 years of experience building analytical and quantitative analysis models.
• 6 years of experience preparing data for prescriptive and predictive modeling.
• 6 years of experience with and understanding of different approaches and methods for data analytics and data science (e.g., complex statistical modeling).
• 6 years of experience with Artificial Intelligence (AI) or Machine Learning (ML) applied to data science or analytics, such as using ML for anomaly detection, predictive monitoring, or AI-assisted data transformation and automation.

Nice to Have

• 5 years of experience and knowledge of data sharing, data-linkage, de-identification, metadata, data quality, ethics, synthetic data, and data literacy, and how to promote use of government data.
• 5 years of experience combining raw data from a variety of data sources within and across domains.
• 5 years of experience understanding complex business questions and framing the right analytical question to solve a business problem.
• 5 years of experience preparing visualizations, dashboards, and analytical models.
• 6 years of experience with and understanding of statistical and data mining techniques to address key business issues.
• 4 years of experience working with large government datasets.

Mindtris, a minority women-owned enterprise, is at the forefront of digital transformation, technology excellence, and business growth solutions. Specializing in talent mobilization and innovation, we are dedicated to enhancing customer experiences across diverse sectors such as Information Technology, Telecommunications, Healthcare, Engineering, and the Public sector. With a focus on deploying top-tier talent and fostering innovation, we empower businesses to thrive and excel in a rapidly evolving digital landscape, helping them reach new heights of success.

Mindtris is committed to fostering workforce diversity and is proud to be an equal opportunity employer.