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Added 4 days ago
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Identity Digital Inc.

Data Scientist & Machine Learning Engineer

Toronto, ON, Canada

Pay: $87,000 to $114,000 CAD / year
Job type: Full-time
Apply by: Oct 16, 2026
Education: Bachelor’s degree
Experience: 3+ years of experience in developing, deploying, and monitoring production data / ML pipelines
Posting language: English
Posted: Sep 16, 2026

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Original job description

Summary / Objective

The Data & Analytics team builds and manages data systems, analyzes information to generate insights, and develops machine learning models to support automated decisioning. As a Data Scientist and Machine Learning Engineer, you will work across (and connect) the expertise of these two related but distinct disciplines. Your responsibilities will include (but not be limited to): deriving data insights to drive decision making, applying ML and modeling techniques to solve business problems, and deploying and managing those models in production.

This role reports to the Director of Business Intelligence.

What You'll Do

Translate complex business problems into data, modeling, and machine-learning solutions
Collect, clean, transform, and validate data for analysis and model development
Explore data to identify patterns, trends, anomalies, and actionable insights
Design, train, evaluate, and refine predictive or optimization models
Select appropriate features, algorithms, metrics, and validation strategies
Build reproducible data and machine-learning pipelines
Deploy models for batch or real-time inference
Develop and maintain infrastructure for reliable model serving
Monitor model performance, data quality, drift, latency, and operational health
Communicate findings and collaborate with stakeholders, engineers, and domain experts
Actively models and promotes Identity Digital’s core values through day-to-day interactions, behaviors, and decision-making
Other duties as assigned

Who You Are / What You Bring

3+ years of experience in developing, deploying, and monitoring production data / ML pipelines
Bachelor's Degree in Mathematics, Computer Science, Data Science, Engineering or other quantitative field is required; Advanced degree (Masters or PhD) in AI/ML preferred
Deep technical knowledge in several of the following topics: anomaly detection, time-series analysis, structured and unstructured data processing, causal inference, reinforcement learning, embeddings and vector databases, large language models, and modern MLOps / LLMOps practices
Professional development experience with the following tools and platforms: Airflow, Argo Workflows, cloud data warehouses (BigQuery, Databricks, Snowflake), major cloud providers (AWS, GCP), Git, Kubernetes, MLFlow, Pandas, Polars, PyTorch, TensorFlow, SHAP and leveraging AI / LLMs.
Strong programming proficiency in Python and SQL; familiarity with Shell scripting is a plus
Exceptional problem-solving skills with the ability to diagnose and resolve issues from limited or ambiguous information
Creative and strategic thinker with a strong analytical foundation and a focus on measurable impact
Collaborative communicator who excels in cross-functional environments and builds strong working relationships
Highly organized with excellent time management, attention to detail, and execution discipline
Knowledge of the domain name industry or digital identity ecosystem is a plus
Ability to travel as needed
Ability to work across time zones as part of a global organization as needed
Reliable transportation to the workplace

Physical Requirements

Prolonged periods of sitting at a desk and working on a computer
Must be able to lift up to 15 pounds at times

Salary Range

The base salary range for this full-time position is CAD $87,000 - $114,000 (flexibility based on experience) plus additional benefits. In addition, the successful candidate will be eligible to receive other compensation from time to time in the form of discretionary and/or nondiscretionary bonuses and long-term incentive plan. Actual compensation will be influenced by a candidate’s qualifications, internal employee equity considerations, and location. We will not ask for information about a candidate's current or past compensation for purposes of developing an offer of employment.

Note: Benefits programs are subject to eligibility requirements and may vary in certain locations.

A few things to know about us

Identity Digital is an Equal Opportunity Employer and does not discriminate based on race, color, religion, sex, age, national origin, veteran status, marital status, sexual orientation, gender identity, disability or any other category prohibited by local, state or federal law. This policy applies to all aspects of employment, including recruitment, placement, promotion, transfer, demotion, compensation, benefits, social and recreational activities, and termination.

Background Check Statement

At the time of an offer, you will be required to complete a background check. Any offer is contingent upon a satisfactory background check.

Sponsorship Statement

Please note that work sponsorship for this position may not be available now or in the future. While we strive to support our candidates, not all roles will qualify. Eligibility will be reviewed on a case-by-case basis.

Accommodation Statement

We are committed to the full inclusion of all qualified individuals. As part of this commitment, Identity Digital will ensure that persons with disabilities are provided reasonable accommodations. If reasonable accommodation is needed to participate in the job application or interview process, please contact our Recruiting Team at [email protected].

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More about this job

Responsibilities

The role involves translating business problems into machine learning solutions and building reproducible data pipelines. Responsibilities include designing, deploying, and monitoring predictive models in production to drive automated decision-making.

Requirements

Requires a Bachelor's degree in a quantitative field and 3+ years of experience in production ML pipelines. Proficiency in Python, SQL, and modern MLOps tools like Kubernetes and Airflow is essential.

Skills

Machine Learning
Data Science
Python
SQL
MLOps
LLMOps
Data Pipeline Development
Predictive Modeling
Cloud Data Warehousing
Kubernetes
PyTorch
TensorFlow
Airflow
Time-series Analysis
Anomaly Detection
Causal Inference

Benefits

Discretionary bonuses
Nondiscretionary bonuses
Long-term incentive plan

Visa sponsorship

Not detected in the job text

Keywords

Data Science
Machine Learning
MLOps
LLMOps
Python
SQL
Airflow
Argo Workflows
BigQuery
Databricks
Snowflake
AWS
GCP
Git
Kubernetes
MLFlow
Pandas
Polars
PyTorch
TensorFlow
SHAP
Large Language Models
Vector Databases
Embeddings
Reinforcement Learning
Causal Inference
Time-series Analysis
Anomaly Detection
Digital Identity
Domain Name Industry

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