Top Data Science Jobs in Calgary

Develop enterprise customers’ automation strategies, identify and deploy high-value AI-enabled use cases, quantify ROI, and drive adoption, renewal, and expansion. Build executive and stakeholder relationships, advise on governance and scalable orchestration, coordinate internal and customer teams, interpret usage data, and create repeatable methodologies and playbooks for Zapier’s enterprise customer success program.

Owns the strategy and roadmap for Duck Creek’s billing product domain, including invoicing, payments, collections, commissions, disbursements, reconciliation, and automation. Partners with engineering, architecture, data, finance, sales, and customers to deliver configurable, scalable, compliant, and explainable billing capabilities. Leads discovery, prioritization, AI-enabled decision support, governance, adoption, and financial outcomes for insurance billing workflows.

Cygnus Professionals Inc. is hiring experienced .NET Developers to work in their IT Solutions Division, providing various IT services and solutions.

Own production-grade analytics pipelines from design through maintenance, build dbt-based analytical models using Kimball dimensional modeling, and deliver reliable data features. Partner with Product, Engineering, and Data Science teams to translate retail signals into business insights. Establish standards for monitoring, documentation, reproducibility, and code quality. Use AI tools to accelerate development and prototype conversational data experiences for natural-language retail data exploration.

Participate in two 12-month rotations supporting Finance and Merchandising through data science, business intelligence, data engineering, visualization, and finance transformation. Develop dashboards, reports, models, and data-driven solutions; analyze business problems; modernize financial data processes; and integrate AI tools to automate workflows and generate actionable insights. Collaborate cross-functionally with Finance, analytics, and external teams in a primarily onsite Calgary environment.

Two-year rotational data science program supporting Finance and Merchandising through business intelligence, data engineering, analytics, visualization, finance transformation, and AI development. Associates will build dashboards, models, data-driven solutions, intelligent agents, and decision-support insights while collaborating cross-functionally. The role is based in Calgary and requires four days onsite weekly.

OneSix is seeking motivated professionals for future opportunities in data and AI consultancy. Interested candidates should submit their resumes to stay in touch.

The Head of AI will define and execute an AI roadmap, lead research initiatives, mentor the AI team, and collaborate with senior leadership to enhance health technology.

Lead the development, validation, and maintenance of clinical data programming solutions for EDC/CDMS systems, vendor data, analytics, reports, integrations, and data transfers. Provide technical leadership across studies, serve as a programming subject matter expert, mentor programmers, support study teams, and drive automation and process improvements. Collaborate with data managers, biostatisticians, and project managers to ensure high-quality clinical trial data management solutions.

Develops, validates, and maintains clinical data programming solutions for CDMS and clinical trials, including eCRFs, edit checks, data validation outputs, reports, extracts, transfers, and vendor data programs. Collaborates with cross-functional clinical data teams, supports study setup and maintenance, mentors junior programmers, creates training materials, and improves technical systems and processes.

As a Senior/Staff Machine Learning Engineer, you will design scalable data pipelines, implement ML algorithms, and collaborate with engineers and Data Scientists to optimize the digital advertising platform.

As an Automation Engineer, you'll build automation pipelines, collaborate on experimental needs, program instrumentation, and integrate with data science, enhancing research capabilities.

Lead product strategy and execution for Clio's enterprise suite (Vincent and Operate). Define roadmaps, partner with Design, Engineering, Research, and Data Science, embed user research and data-informed decisions, and mentor other product managers. Drive AI-enabled product development, customer engagement, and cross-functional alignment to deliver enterprise-grade legal solutions.

As a founding Data Scientist/Machine Learning Engineer, you'll develop AI/ML models, enhance product capability, and drive impactful user outcomes while working closely with product teams.

Leads MAU analytics and data science, managing decision scientists and data scientists while setting quality standards. Owns MAU driver modeling, forecasting, causal analysis, experimentation, and exploratory work supporting growth strategy. Establishes consistent analytical practices, partners with revenue, product, engineering, and data engineering leaders, and embeds the team in roadmap planning. Promotes AI-native workflows through coding agents, automation, and analytical tools while coaching team members into strategic advisors.

The Forward Deployment Engineer will deploy and optimize Generative AI solutions, architect scalable infrastructure, and implement data pipelines across multi-cloud environments while collaborating with cross-functional teams to maximize business value.

Lead Mozilla’s Marketing Data Science strategy and roadmap for Firefox. Drive attribution, ROI, campaign measurement, budget optimization, causal lift testing, brand impact analysis, retention and LTV modeling, audience segmentation, reporting infrastructure, dashboards, and scalable data tools. Mentor and develop team members, partner with cross-functional data science and marketing leaders, translate complex analyses into actionable recommendations, and evaluate emerging AI tools to improve workflows and business impact.

The Engineering Leader will oversee software and data teams, ensuring product delivery and operational excellence in robotics and IoT systems.

Evaluate and label model-generated and human-written code outputs, debug and assess code/agent trajectories, prompt models for complex data science tasks, review visualizations, and report quality trends to improve model behavior.