Data Scientist

Overview

POSITION SUMMARY The Data Scientist designs, builds, and operationalizes analytical solutions that deliver measurable business outcomes. You will translate ambiguous problems into clear hypotheses, prepare and engineer data, develop and validate models, and partner with engineers and stakeholders to deploy solutions into production. This role is hands-on and outcomes-focused, accelerating our clients’ AI and analytics journeys across use cases in customer intelligence, risk, operations, and beyond.

Primary

Location:

Across Canada

Work Model: Hybrid 2-Days Onsite

Employment Type: Permanent Full-Time

Vacancy Status: Pipeline Requisition

Compensation Range: CAD 100,000 – 140,000/yr base salary

• Gather business requirements and frame data science use cases with measurable success criteria
• Perform data discovery, profiling, cleaning, and feature engineering across large, complex datasets
• Build, evaluate, and iterate on supervised and unsupervised ML models (e.g., classification, regression, clustering)
• Implement robust experimentation, validation, and statistical testing to ensure model quality and reliability
• Collaborate with data engineers to design scalable ETL/ELT and model serving pipelines
• Optimize code and queries for performance, cost, and maintainability in cloud environments
• Create clear, executive-ready narratives and visualizations to communicate insights and recommendations
• Contribute to productionization with MLOps teams (packaging, CI/CD, monitoring, model drift detection)
• Follow engineering best practices: version control, code reviews, unit testing, documentation
• Stay current on ML/AI techniques and bring practical innovations into client projects

• Bachelor’s degree in quantitative field (Computer Science, Engineering, Mathematics, Statistics, or related)
• 4+ years of hands-on experience building and deploying ML models end-to-end (problem framing → data prep → modeling → validation → documentation → deployment)
• Proficiency in Python (Pandas, Num Py, scikit-learn) and strong SQL for data manipulation and performance tuning
• Solid understanding of data modeling, feature engineering, and evaluation metrics for supervised/unsupervised learning
• Experience working with large datasets and modern data ecosystems (cloud data warehouses, files/object storage)
• Ability to communicate complex analytical findings to technical and non-technical audiences and drive stakeholder alignment

• Experience with big-data and distributed computing frameworks (e.g., Spark, PySpark) and/or Databricks
• Exposure to cloud analytics services (AWS, Azure, or GCP) and orchestration (e.g., Airflow, ADF, Glue)
• Familiarity with MLOps practices (model packaging, CI/CD, observability, drift monitoring)
• Experience in consulting or client-facing roles, translating business needs into technical deliverables

• Experience with NLP, time-series, or recommendation systems
• Knowledge of experiment design, causal inference, and uplift modeling
• Familiarity with BI/visualization tools (e.g., Power BI) and storytelling techniques
• Exposure to SAS (e.g., SAS Viya) for analytics in regulated environments

Adastra is a global leader in AI and data-driven transformation, helping organizations lead with artificial intelligence—responsibly, strategically, and h over 25 years of experience, Adastra empowers enterprise clients to unlock business value through data innovation, operational excellence, and smart customer engagement.

Trusted by some of the world’s most prominent brands, Adastra delivers end-to-end solutions grounded in thoughtful strategy, robust governance, and deep technical expertise. From defining vision to ensuring execution, Adastra guides organizations through every stage of their AI, data and cloud journey—building future-ready capabilities and delivering measurable, lasting impact.

Adastra serves clients across key industries including financial services, automotive, manufacturing, technology, media and telecom (TMT), healthcare, retail, and professional services. The company employs more than 2,000 professionals across North America, Europe, and Asia.