Scientifique des données III-Ingénieur; Data Scientist III-Eng

UKGMontreal, QC
CA$110,400 - CA$149,000Hybrid

About The Position

As a Data Scientist III, you will design, develop and deliver innovative data science solutions spanning our UKG product domain. You will own projects from problem definition through production deployment to build scalable systems that drive measurable business impact. This senior IC role combines deep technical expertise with project leadership and mentorship to drive UKG’s AI innovation roadmap. The ideal candidate will work from our Montreal office three days a week.

Requirements

  • Advanced degree (MS or PhD) in a quantitative field or equivalent industry experience
  • 5-7+ years’ experience in a software product environment, with at least 3 years’ hands-on experience as a Data Scientist. Proven experience in building, training, and deploying ML models in a production environment.
  • Deep familiarity with Python (pandas, scikit-learn, PySpark), SQL/BigQuery, and version control
  • Hands-on experience with cloud-based ML infrastructure (AWS/GCP/Azure) and MLOps workflows
  • Strong understanding of statistical modeling, experimentation, and evaluation frameworks
  • Deep expertise in one or more ML domains such as NLP, deep learning, time-series, or clustering
  • Hands-on experience building services and solving problems using LLMs and generative AI techniques preferred
  • Ability to operate independently, think strategically, ensure execution and influence others
  • Proven ability to effectively communicate with all levels of the organization.

Responsibilities

  • Apply rigorous statistical and machine learning techniques to analyze billions of workforce management and HCM records and identify meaningful product and feature opportunities
  • Develop and deploy modern Data Science/AI solutions including generative AI applications, RAG systems, and agentic workflow
  • Establish evaluation frameworks to measure model quality and business impact
  • Lead the research, design, and implementation of end-to-end ML/AI pipelines in development and production environments
  • Own the full model lifecycle: validation, deployment, monitoring, and iteration
  • Ensure reliability, performance, and maintainability of AI systems in partnership with engineering teams
  • Write high-quality, modular production code and design clean data/model pipelines
  • Collaborate with engineering partners on CI/CD, observability, and scaling strategies
  • Partner with Product Managers and domain experts to translate business requirements into scalable solutions
  • Communicate model outcomes and insights effectively to technical and non-technical stakeholders
  • Mentor junior data scientists through code reviews, model reviews, and modeling best practices
  • Proactively identify opportunities to improve team capabilities and development standards

Benefits

  • flexibility that’s real
  • benefits you can count on
  • performance-based bonus plan
  • restricted stock unit awards
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