Job Title: DataIku Data Scientist – Machine Learning & Advanced Analytics
Location: Scarborough, ON (hybrid)
Duration: 12-14 months contract with possible extension
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, optimize 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 operationalize 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 analyze 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 modeling, 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: Apache Spark
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 operationalizing: Classification models
Recommendation systems
Predictive analytics solutions
Anomaly detection models
Time-series forecasting models

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
Azure Machine Learning
Databricks

Strong experience with enterprise data platforms including: Netezza
Amazon Redshift
SQL Server/relational databases

Experience with MLOps practices, model governance, model monitoring, and production deployment frameworks.
Familiarity with CI/CD, containerized 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.
Experience developing models for: Incident prediction
Change-induced outage prediction
Root cause analysis
Event correlation
Recommendation systems

Solid 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
Azure AI / Generative AI solutions
Feature Store implementation
LLM and Agentic AI frameworks

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📌 Data Scientist (Ontario)
🏢 SPECTRAFORCE
📍 Ontario