Senior Data Scientist

Do you get excited when a messy, ambiguous business problem finally yields to the right model? Do you think in systems, speak fluently across the technical-business divide, and want your work to do more than sit in a notebook — you want it to actually ship, scale, and matter?

With over 2,000 employees, 36 offices on five continents, and world-class clients like Samsung, L'Oréal, and Mattel, Artefact is a consulting firm that transforms data into measurable value and business impact. We've launched in the US with offices in NYC and Los Angeles — and we're looking for a Senior Data Scientist to help define what world-class data science looks like on our founding team.

Founded and headquartered in Paris, Artefact is a next-generation consulting firm specializing in data, analytics, and AI consulting — dedicated to transforming data into business impact across the entire value chain of organizations. We don't just advise; we build, implement, and deliver results our clients can measure.

We have 2,000 employees across 36 offices focused on accelerating digital transformation for some of the world's most recognizable brands. Our state-of-the-art data technologies, lean AI agile methodologies, and cohesive teams of elite business consultants, data analysts, data scientists, data engineers, and digital experts are all laser-focused on delivering real value to every client. We design data-driven solutions tailored to each client's specific needs — always conceived with a business-first mindset and delivered with tangible, measurable results. Our expertise is built on deep AI knowledge acquired through 1,000+ client engagements across the globe.

Find out more at artefact.com.

As a Senior Data Scientist, you'll be the technical engine behind some of our most complex and consequential client engagements. You'll move fluidly between data exploration, model development, and executive communication — bringing scientific rigor to business problems and translating results into strategies that clients actually implement.

This isn't a role where you hand off findings and walk away. You'll be embedded with clients, co-owning outcomes, and ensuring that the models you build don't just perform in a test environment — they create real, lasting impact in production. You'll also be a technical anchor for our US team, setting standards, mentoring junior data scientists, and contributing to the methodologies that define Artefact's edge.

• →Designing and building end-to-end machine learning and statistical models that solve high-stakes business problems — from framing the question to deploying the solution
• →Conducting rigorous exploratory data analysis to uncover patterns, anomalies, and opportunities that inform both technical and strategic decisions
• →Translating complex model outputs and analytical findings into clear, compelling narratives for senior client stakeholders — making the technical accessible without dumbing it down
• →Partnering with client teams and data engineers to ensure models are production-ready, scalable, and built on clean, reliable data pipelines
• →Defining the analytical approach for client engagements — selecting the right methods, tools, and frameworks for the problem at hand, not just the ones you're most comfortable with
• →Contributing to new business proposals — helping articulate Artefact's technical capabilities and translating data science into clear client value
• →Developing thought leadership and internal methodologies — publishing research, building reusable frameworks, and raising the technical bar across the practice
• →Mentoring junior data scientists and analysts, actively investing in the team's technical depth and growth

We want someone who is as comfortable whiteboarding a modeling strategy with a client's Chief Analytics Officer as they are debugging a pipeline at 11pm before a big delivery. You've shipped models that people actually use. You've sat in rooms where the business stakes were real, and you've delivered. You know the difference between a technically elegant solution and a practically useful one — and you always choose useful.

You'll arrive ready with the following:

• 4–7 years of hands-on experience in data science, machine learning, or advanced analytics — with a demonstrable track record of end-to-end model delivery in a client-facing or high-stakes business environment
• Advanced degree (MSc or PhD) in a quantitative field — statistics, mathematics, computer science, engineering, or equivalent; strong undergraduate candidates with exceptional experience will be considered
• Expert-level proficiency in Python and/or R; you write clean, maintainable, production-quality code
• Deep expertise in machine learning and statistical modeling — regression, classification, clustering, time series, NLP, recommendation systems, and/or deep learning, depending on your specialization
• Strong command of SQL and experience working with large-scale datasets across cloud platforms (GCP, AWS, or Azure)
• Experience with MLOps practices — model versioning, monitoring, deployment pipelines, and productionization — is a significant differentiator
• Exceptional communication skills — you can explain a gradient boosting model to a CFO and a business case to an ML engineer, and both conversations land
• Demonstrated ability to lead technical workstreams and mentor junior team members
• Consulting or client-facing experience is highly desirable; the ability to manage ambiguity, scope problems, and deliver under pressure is essential
• Exposure to marketing analytics, customer analytics, or demand forecasting in a consumer-facing industry is a meaningful asset

At this level, you're not just looking for a job — you're looking for the right environment to do your best work. Here's what makes Artefact different:

Variety that keeps you sharp. In a product role, you go deep on one problem. Here, you'll work across industries, business functions, and problem types — building the kind of range that makes exceptional data scientists exceptional. No two engagements are the same.

Your work actually ships. We have a relentless focus on adoption and impact. The models you build are designed from day one to live in production, influence decisions, and create measurable value — not to gather dust in a final report.

A global technical community. With 2,000 data and AI specialists across 36 offices, you'll have access to some of the most sophisticated data science thinking in the world. You'll contribute to — and benefit from — a community of practitioners working on the frontier.

Founding team energy. We're building our US practice, which means the norms, standards, and culture you help create now will define Artefact in North America for years to come. That's a rare opportunity at any stage of a career.

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

• There is always a way — We're builders, diggers, and makers. Ideas only count if they get executed.
• Client trust is won in the field — We show up where it matters, working side by side with our clients to solve what's real.
• If not used, it is useless — We build for adoption and impact. True brilliance is measured by what changes, not what's delivered.
• If not shared, our work is not done — Sharing knowledge is how we close the loop — for our clients and for each other.
• We learn every day — In a field moving at the speed of light, intellectual curiosity isn't optional. It's survival.