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