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Senior, AI & Data Science

Montréal, Quebec, Canada

Live, first seen by us 76 days ago
Pay
Pay not listed
Work setting
Not stated
Employment
Full-time — employment source
Employment type in the employer’s posting: Full-time
From the employer’s posting

What you’ll work on

Full posting
  • Translate business and marketing challenges into analytical use cases with clear success metrics

  • Develop statistical and machine learning models for forecasting, classification, clustering and causal inference

  • Ship production-ready solutions with training, deployment, monitoring and refinement

  • Run LLM fine-tuning experiments and build evaluation suites for LLM systems

  • Present findings to client stakeholders in business language

From the employer’s posting
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.
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.
Present findings to client stakeholders, translating methodology into business language.

What you’ll bring

All qualifications

Core experience

  • 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).
  • Master's degree (or higher) in statistics/mathematics, engineering, computer science, economics, or a related field, or equivalent experience.
Qualification wording
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).
Master's degree (or higher) in statistics/mathematics, engineering, computer science, economics, or a related field, or equivalent experience.
Education & alternatives
- 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:

About LinkedIn Job Wrapping

We are proud to say that we help our clients grow their data and digital capabilities, and that we’re also growing in parallel.

In the employer’s words · Read in context

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Posting record

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Status in our records
Live
First seen by us
Aug 20, 202676 days ago
Recorded sightings
58
Last seen by us
Nov 5, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 76

Up longer than most. Similar jobs usually come down between day 7 and day 56.

At LinkedIn Job Wrapping, jobs usually come down by about day 62.

From 10,201 similar postings that came down, and 19 of LinkedIn Job Wrapping’s. Coming down is not always a hire.

LinkedIn Job Wrapping is hiring

24 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Hiring has slowed
  • Its jobs tend to stay up a long time
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • AWS
  • Azure
  • GCP
  • Hugging Face
  • PyTorch
  • scikit-learn
  • Transformers
  • XGBoost
Where the posting names them
- 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).
- 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.
- MLOps exposure: model versioning, pipelines, monitoring. - Cloud certifications, especially Google Cloud Professional Machine Learning Engineer. -
- Causal inference, time series, or advanced statistics experience. - Hugging Face Transformers, LoRA/PEFT, or open-weight model experience. - MLOps exposure: model versioning, pipelines, monitoring.

Your next step

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Demand for Data Scientist roles

New Data Scientist postings at the employers we follow are down 3% over the last 5 weeks compared with the 5 before.

Weekly new Data Scientist postings at the same employers, from the week of August 17 to the week of October 26. The fewest in a week was 1,411, the most 2,973, and the latest week had 1,826.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 5 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under Data Scientist, by the work the posting describes.

Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.

Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.

Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.

US government figures for data scientists

Median yearly pay, May 2025
$120,230
Expected change, 2025 to 2035
34.6% more jobsagainst 3.5% for all jobs

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.

Job description

View original posting ↗

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.

 

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Location & working pattern

Montréal, Quebec, Canada

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.
More source context
- 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.
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