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Director Of Data Science Jobs in Quebec (NOW HIRING)

We sit at the intersection of consulting, data science, AI technologies, data engineering, and digital transformation. We do not just advise - we build, implement, and deliver results our clients can ...

Our employees are at the heart of everything we do. Together, we help people, businesses, and ... Data science enthusiasts with a background in a related field, including (but not limited to ...

Keep abreast of the latest trends and methodologies in data science and integrate them into your work. * Tool and platform maintenance: Help maintain and improve our data mining tools and platforms ...

Improving quality of life around the world through software and services that increase the ... HOW YOU'LL MAKE A POSITIVE IMPACT As part of the Data Science Development team, you will contribute ...

Use data science techniques to find data patterns, anomalies, and optimization opportunities. * Execution, evaluation, and reporting of A/B testing amp; cross-validating models to ensure their ...

The role will be responsible for delivering high quality data science models, and the logistical challenges around improving a profitable service. You'll also be working on a diverse range of supply ...

The role will be responsible for delivering high quality data science models, and the logistical challenges around improving a profitable service. You'll also be working on a diverse range of supply ...

Data Science, Data Engineering, Data Architecture, and Data Analytics . You are simultaneously the architect of the data factory and the director ensuring it delivers high-value outputs to the ...

Minimum of 2 years of experience in data science, machine learning and advanced statistics solving business problems. * Technical Skills: Proficiency in multiple platforms, including commercial and ...

Toronto, Ontario, Canada Hours: 37.5 Line of Business: Analytics, Insights, & Artificial ... Lead cross-functional collaboration with data scientists, engineers, IT partners, and business ...

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Director Of Data Science information

What are some common challenges faced by a director of data science when leading cross-functional teams?

As a Director of Data Science, one of the key challenges is aligning the goals of data science teams with those of product, engineering, and business stakeholders. This often involves translating complex technical findings into actionable insights that non-technical colleagues can understand and use. Additionally, managing resource allocation and prioritizing projects across multiple departments can be demanding, especially in fast-paced environments. Building a collaborative culture and fostering open communication are crucial for overcoming these challenges and ensuring data-driven strategies deliver business value.

What are the key skills and qualifications needed to thrive as a director of data science, and why are they important?

A Director of Data Science needs advanced expertise in statistical analysis, machine learning, and data strategy, typically supported by a graduate degree in a quantitative field and significant industry experience. Familiarity with big data platforms (e.g., Hadoop, Spark), programming languages (Python, R), and cloud-based analytics tools, as well as experience managing data science teams, is essential. Strong leadership, communication, and business acumen are key soft skills for aligning technical work with organizational goals and influencing stakeholders. These skills are crucial for driving data-driven decision-making and maximizing the strategic impact of data science initiatives within the organization.

What is the difference between Director Of Data Science vs Data Scientist?

AspectDirector Of Data ScienceData Scientist
Required CredentialsAdvanced degrees (Master's or PhD), leadership experienceBachelor's or Master's in Data Science, Computer Science, or related fields
Work EnvironmentStrategic planning, team management, cross-department collaborationData analysis, model development, coding, and experimentation
Employer & Industry UsageTech companies, finance, healthcare, large enterprisesStartups, tech firms, research institutions, various industries

The main difference between a Director Of Data Science and a Data Scientist lies in their scope of responsibilities. The Director oversees strategic initiatives, manages teams, and aligns data projects with business goals, while Data Scientists focus on analyzing data, building models, and deriving insights. Both roles require strong technical skills, but the Director's role emphasizes leadership and strategic planning.

What does a director of data science do?

A director of data science oversees data science teams, develops strategies for data analysis and modeling, and ensures the implementation of data-driven solutions to support business goals. They often manage projects, collaborate with other departments, and have expertise in statistical methods, machine learning, and data management tools. Strong leadership, communication skills, and experience with programming languages like Python or R are essential for this role.
Infographic showing various Director Of Data Science job openings in Quebec as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution.

Senior, AI & Data Science

Montreal, QC

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 9 days ago


Job description

About the job

Artefact is a next-generation data and AI consulting firm dedicated to accelerating the adoption of data and AI to create measurable business impact across the full enterprise value chain.We sit at the intersection of consulting, data science, AI technologies, data engineering, and digital transformation. We do not just advise - we build, implement, and deliver results our clients can measure. Our teams bring together consultants, data scientists, data engineers, AI engineers, analysts, and digital experts to solve complex business challenges with pragmatic, production-ready solutions.

As Artefact continues to grow in the US, we are building a team of entrepreneurial data and AI talent who can help clients move beyond experimentation and into scalable, governed, value-generating AI adoption.

Who We Are

Founded and headquartered in Paris, Artefact is a next-generation consulting firm, specializing in data, analytics & AI consulting, dedicated to transforming data into business impact across the entire value chain of organizations. We are proud to say that we help our clients grow their data and digital capabilities, and that we're also growing in parallel.

We have 2000 employees across 36 offices who are focused on accelerating digital transformation. Our state-of-the-art data technologies, lean AI agile methodologies, and cohesive teams of the finest business consultants, data analysts, data scientists, data engineers, and digital experts are all dedicated to bringing extra value to every client. We design data-based solutions to meet our clients' specific needs, always conceived with a business-centric approach and delivered with tangible results. Our data-driven services are built upon the deep AI expertise we've acquired with our 1000+ client base around the globe.

Find out more at artefact.com.

What you will be doing 

Artefact is looking for a Senior AI & Data Scientist: a scientist who owns models end to end, from problem framing through production.

You will work across the full modeling spectrum - forecasting, classification, clustering, and causal analysis on one engagement; fine-tuning experiments and LLM evaluation on the next. You will own your models: the data behind them, the methodology, the deployment, and the story told to the client. You will also help junior scientists grow.

  • Translate business and marketing challenges into analytical use cases with clear hypotheses and success metrics.
  • Develop statistical and machine learning models: regression, forecasting, classification, clustering, and causal inference.
  • Select techniques based on business context, constraints, and data availability - and be able to justify the choice.
  • Ship production-ready solutions: training, deployment, monitoring, and ongoing refinement.
  • Run fine-tuning experiments: dataset curation, SFT, LoRA/PEFT, and rigorous evaluation of results against baselines.
  • Build evaluation suites for LLM systems: benchmarks, LLM-as-judge patterns, and regression tests.
  • Work with embeddings and retrieval where they affect answer quality.
  • Contribute to model selection decisions: prompting vs. RAG vs. fine-tuning, cost vs. quality vs. latency.
  • Build data pipelines for ingestion, transformation, and quality assurance across diverse data sources.
  • Create clear visualizations and dashboards that support data storytelling and decision making.
  • Present findings to client stakeholders, translating methodology into business language.
  • Mentor junior data scientists and use AI-assisted tools (Claude Code, Gemini CLI) to raise the whole team's pace.

What we are looking for 

  • 3-5 years of relevant data science experience with a substantial quantitative skill set.
  • Strong knowledge of statistics and ML algorithms, with at least one proven experience developing and deploying models.
  • Proficiency in Python (scikit-learn, XGBoost; PyTorch a strong plus) and solid SQL.
  • Hands-on experience with LLMs: evaluation, RAG, or fine-tuning experiments (professional or substantial personal projects).
  • Specialization in at least one major AI platform ecosystem - Google (Gemini, Vertex AI), Anthropic (Claude), or OpenAI - and familiarity with a cloud platform (GCP, Azure, or AWS).
  • Comfort with AI-assisted development tools such as Claude Code, Gemini CLI, or Cursor.
  • Excellent interpersonal and communication skills: you can present methodology and results to non-technical audiences.
  • Master's degree (or higher) in statistics/mathematics, engineering, computer science, economics, or a related field, or equivalent experience.

Preferred: 

  • Causal inference, time series, or advanced statistics experience.
  • Hugging Face Transformers, LoRA/PEFT, or open-weight model experience.
  • MLOps exposure: model versioning, pipelines, monitoring.
  • Cloud certifications, especially Google Cloud Professional Machine Learning Engineer.
  •  

Why Join Us

We are united by our values and strengthened by our hybrid expertise.

  • There is always a way: We're from the breed of does, of diggers, of makers. Because ideas are valuable only if executed.
  • Client trust is won on the field: Addressing client needs flows better hands on at their side.
  • If not used, it is useless: Our love for technology translates into a steep desire for adoption, true brilliance is about impact.
  • If not shared, our work is not done: Sharing knowledge is the best way to button up a mission, benefitting clients and colleagues.
  • We learn everyday: Tech is a land where everything moves at the speed of light, you better be ready to challenge yourself.

How We Support Our People

In addition to our values-driven culture, we offer a range of benefits and programs designed to support our employees' growth and well-being, including:

  • Learning and Development: Work alongside a multidisciplinary team of AI, data, and consulting experts who are committed to continuous learning, knowledge sharing, and professional growth.
  • Hybrid Flexibility: Our hybrid work model gives you the flexibility to balance collaboration, client needs, and personal commitments.
  • Comprehensive Benefits: We offer a competitive benefits package that includes medical, dental, and vision coverage, a 401(k) plan with company matching, and paid parental leave.
  • Time to Recharge: We believe sustainable performance matters. That's why we offer unlimited paid time off, giving you the flexibility to take the time you need.
  • Growth Opportunities: As a rapidly growing organization, you'll have the opportunity to expand your skills, take on new challenges, and help shape the future of the company.