Senior Data Scientist

About this role

About the Job

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.

Who We Are

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.

What You Will Be Doing

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.

Key responsibilities include:

• 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

What We Are Looking For

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…