Data Scientist

Job Title: DataIku Data Scientist – Machine Learning \& Advanced Analytics

Location: Scarborough, ON (hybrid)

Duration: 12-14 months contract with possible extension

*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.*

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