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?

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 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

Compensation & Benefits

The 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.