Data Scientist – Machine Learning & Advanced Analytics

SPECTRAFORCE; Toronto; Hybrid; CAD 120,000 - 160,000; Full time

Job summary

SPECTRAFORCE in Toronto, ON is seeking a Data Scientist to lead the design, development, and productionalization of advanced ML solutions across the enterprise.

You will leverage large-scale structured and unstructured data to deliver predictive insights, improve processes, and enable data-driven decision making across the organization.

The role requires strong ML expertise, Dataiku DSS, and exposure to Azure AI/LLMs, with a hybrid (Toronto area) or remote work arrangement available.

Qualifications

• 7+ years of experience in Data Science, ML, AI, or related analytics.
• Strong proficiency in Python (preferred) or SAS for statistical modelling and data analysis.
• Expert-level SQL skills with hands-on experience with large-scale enterprise datasets.
• Hands-on experience with Dataiku DSS for modeling and deployment.
• Experience with ITSM data (ServiceNow, Dynatrace, CMDB).
• Proficiency in Power BI and data visualization.

Responsibilities

• Design, develop, deploy, and maintain ML, DL, and AI-driven solutions addressing complex business challenges.
• Build scalable predictive and prescriptive analytics models using large-scale datasets to improve performance and operations.
• Translate business needs to technical specifications and evaluate data visualization systems.
• Perform advanced data exploration, feature engineering, model development, validation, and monitoring.
• Develop end-to-end ML pipelines including data ingestion, training, scoring, scheduling, monitoring, and retraining.
• Utilize big data technologies and distributed computing for high-volume data processing.
• Collaborate with stakeholders to identify opportunities where AI/ML delivers measurable value.
• Conduct statistical analysis, experiments, and model evaluation to uncover trends and insights.
• Research emerging AI technologies to drive innovation and continuous improvement.
• Develop recommendation engines, forecasting solutions, and anomaly detection frameworks.

Skills

Python

SQL

ML/AI

Dataiku

Big Data

Power BI

ITSM analytics

Azure

SAS

DataOps

Tools

Dataiku DSS

ServiceNow

Databricks

AWS SageMaker

Hadoop

Redshift

SQL Server

Power BI

Job description

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 clear insights and recommendations for senior leadership and executive stakeholders.
• Partner with various line of business teams, Data Engineering, DevOps, 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.
• Strong 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 ServiceNow incident, change, problem, CMDB, Dynatrace and other operational datasets.
• Power BI and advanced data visualization
• ServiceNow 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 SageMaker
• 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.