Job Title: Data Scientist – Machine Learning & Advanced Analytics
Location: Toronto, ON/Scarborough, ON (hybrid preferred, open for remote too)

Duration: 6-month contract

Ideal Candidate: A Data Scientist with strong ML expertise , mandatory Dataiku experience, hands‐on AIOps/ITSM analytics , and exposure to Azure AI/LLMs who can contribute to both current predictive analytics initiatives and the team's long-term AI strategy.
Summary

We are seeking a Data Scientist to join our team to lead the design, development, and operationalization of advanced machine learning solutions. The successful candidate will leverage large‐scale structured and unstructured data to deliver predictive insights, optimise business processes, and enable data‐driven decision making across the enterprise.

Key Responsibilities

Design, develop, deploy, and maintain machine learning, deep learning, and AI‐driven solutions that address complex business and operational challenges.

Build scalable predictive and prescriptive analytics models using large‐scale datasets to improve business performance, customer experience, operational efficiency, and risk management.

Translates business needs to technical specifications and evaluates existing data visualization systems to improve them

Perform advanced data exploration, feature engineering, model development, validation, and performance monitoring across the model lifecycle.
Develop and operationalise end‐to‐end ML pipelines, including data ingestion, model training, scoring, scheduling, monitoring, and retraining.
Leverage big data technologies and distributed computing frameworks to process and analyse high‐volume datasets efficiently.
Collaborate with business stakeholders, product teams, and technology partners to identify opportunities where AI/ML can create measurable business value.




Conduct statistical analysis, experimentation, and model evaluation to identify trends, anomalies, and actionable insights.
Research and evaluate emerging technologies, algorithms, and data science methodologies to drive innovation and continuous improvement.
Develop recommendation engines, classification models, forecasting solutions, and anomaly detection frameworks to support strategic business initiatives.
Translate complex analytical findings into transparent insights and recommendations for senior leadership and executive stakeholders.

Partner with various line of business teams, Data Engineering, Dev Ops, and platform teams to ensure scalable, production‐ready analytics solutions are deployed and maintained.

Required Qualifications & Experience

7+ years of experience in Data Science, Machine Learning, Artificial Intelligence, Advanced Analytics, or a related discipline.
Strong proficiency in Python (preferred) or SAS for statistical modelling, machine learning, and data analysis.

Expert‐level SQL skills with hands‐on experience working with large‐scale enterprise datasets.

Solid experience with Big Data technologies, including: Hadoop ecosystem

Distributed data processing frameworks
Hands‐on experience developing, deploying, monitoring, and maintaining machine learning models within Dataiku DSS.
Strong experience working with ITSM data, including Service Now incident, change, problem, CMDB, Dynatrace and other operational datasets.




Power BI and advanced data visualization

Service Now platform analytics and reporting

Experience building and operationalising: Recommendation systems

Predictive analytics solutions

Experience implementing automated scoring and model deployment pipelines using scheduling and orchestration frameworks.

Hands‐on experience with cloud‐based ML platforms such as: AWS Sage Maker

Databricks

Strong experience with enterprise data platforms including: Amazon Redshift

SQL Server/relational databases
Experience with MLOps practices, model governance, model monitoring, and production deployment frameworks.
Familiarity with CI/CD, containerised deployments, and cloud‐native analytics architectures is considered an asset.
Preferred Qualifications
Experience building AI/ML solutions for IT Operations (AIOps), Service Management, or Operational Intelligence use cases.
Incident prediction
Change‐induced outage prediction
Root cause analysis
Event correlation

Recommendation systems

Strong understanding of software engineering best practices, version control, and collaborative development environments.
Excellent communication and stakeholder management skills with the ability to present complex technical concepts to non‐technical audiences and senior leadership.
Banking experience, particularly large enterprise‐wide initiatives would be an asset.
Nice‐to‐Have Skills
Dataiku MLOps and automation capabilities
Feature Store implementation

LLM and Agentic AI frameworks

This role is ideal for a highly technical data scientist with strong machine learning expertise, Dataiku and Azure experience, and a proven track record of delivering enterprise‐scale AI/ML solutions in complex data environments.

📌 Data Scientist – Machine Learning & Advanced Analytics (Toronto)
🏢 SPECTRAFORCE
📍 Toronto