Senior Data Scientist

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.

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

• 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 work streams 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

Estimated base compensation for this role is $125,000 - $135,000. Individual compensation is determined by skills, qualifications, and experience. In addition, this role is eligible for competitive benefits.