Senior Data Scientist

Artefactus; New York (NY); On-site; USD 125,000 - 135,000; Full time

Job summary

Artefactus, based in New York, is seeking a Senior Data Scientist to join their founding team. The role involves designing end-to-end machine learning models and engaging directly with clients to drive business impact.

You will need 4–7 years of experience, an advanced quantitative degree, and expert proficiency in Python or R. This position offers estimated compensation between $125,000 and $135,000, reflecting skills and experience. Strong communication skills are essential for success.

Qualifications

• 4–7 years of experience in data science or analytics with model delivery.
• Expert-level proficiency in Python and/or R.
• Deep expertise in statistical modeling techniques.

Responsibilities

• Design and build machine learning models that solve business problems.
• Conduct exploratory data analysis.
• Translate analytical findings into narratives for stakeholders.

Skills

Hands-on experience in data science

Proficiency in Python/R

Expertise in machine learning

Communication skills

SQL command

Education

Advanced degree (MSc or PhD) in a quantitative field

Tools

Python

R

SQL

GCP/AWS/Azure

Job description

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.

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.

• 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

• 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

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.