Jr. Data Scientist - (Canada-based)

About the job Do you think like a management consultant, thrive in a startup environment, and can’t stop thinking about the intersection of data, technology, and marketing? With over 2000 employees, offices on five continents, and world-class clients like Samsung, L’Oreal, and Mattel, Artefact is a consulting firm that transforms data into value and business impact. We’ve recently launched in the US with offices located in NYC and Los Angeles, and we want you to join us as an integral part of our founding team! Who We Are Founded and headquartered in Paris, Artefact is a next-generation consulting firm, specializing in data, analytics & Ai consulting, dedicated to transforming data into business impact across the entire value chain of organizations. We are proud to say that we help our clients grow their data and digital capabilities, and that we’re also growing in parallel. We have 2000 employees across 34 offices who are focused on accelerating digital transformation. Our state-of-the-art data technologies, lean AI agile methodologies, and cohesive teams of the finest business consultants, data analysts, data scientists, data engineers, and digital experts are all dedicated to bringing extra value to every client. We design data-based solutions to meet our clients' specific needs, always conceived with a business-centric approach and delivered with tangible results. Our data-driven services are built upon the deep AI expertise we've acquired with our 1000+ client base around the globe. Find out more at artefact.com. What you will be doing In addition to the core Data Science and ML Engineering Team, you will work with different stakeholders to: Translate marketing and business challenges into analytical use cases, assess feasibility, and define clear hypotheses. Develop statistical and machine learning models including regression, forecasting, classification, and clustering to identify performance drivers and predict business outcomes. Build and maintain scalable data pipelines for data ingestion, transformation, and quality assurance across diverse marketing data sources. Develop production ready modeling solutions including model training, deployment, monitoring, and ongoing refinement. Evaluate and select appropriate statistical and machine learning techniques based on business context, constraints, and data availability. Create clear and compelling data visualizations and dashboards to support data storytelling and decision making. Collaborate with cross functional partners in an agile environment and iterate on solutions to maximize business impact. What we are looking for The ideal candidate has a substantial quantitative skill set with 2-3 years of relevant experience. Master's degree (or higher) in statistics/mathematics, engineering, computer science, economics, or a related field. Excellent interpersonal and communication skills Strong knowledge of data science algorithms and at least one proven experience in developing Statistical and ML algorithms Proficient in Python (preferred) and/or R Preferred: Preference in Causal Inference topics, Time Series, Advanced Statistics Cloud technologies (GCP, Azure, AWS) especially Google Cloud Platform Why you should join us We are united by our values and strengthened by our hybrid expertise. There is always a way: We're from the breed of does, of diggers, of makers. Because ideas are valuable only if executed. Client trust is won on the field: Addressing client needs flows better hands on at their side. If not used, it is useless: Our love for technology translates into a steep desire for adoption, true brilliance is about impact. If not shared, our work is not done: Sharing knowledge is the best way to button up a mission, benefitting clients and colleagues. We learn everyday: Tech is a land where everything move at the speed of light, you better be ready to challenge yourself. #LI-Hybrid

The role involves translating marketing and business challenges into analytical use cases, defining hypotheses, and developing statistical and machine learning models to predict business outcomes. Responsibilities also include building scalable data pipelines, deploying production-ready modeling solutions, and creating visualizations for decision-making.

Candidates must possess a substantial quantitative skill set with 2-3 years of relevant experience, ideally holding a Master's degree or higher in a quantitative field like statistics, engineering, or computer science. Essential requirements include strong interpersonal skills and proven experience developing Statistical and ML algorithms, with proficiency in Python or R.

Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.

• Data Science
• Machine Learning Engineering
• Statistical Modeling
• Regression
• Forecasting
• Classification
• Clustering
• Data Pipelines
• Model Deployment
• Model Monitoring
• Data Visualization
• Dashboarding
• Python
• R
• Causal Inference
• Time Series

• Data & Analytics
• Consulting
• Science & Research
• Software
• Marketing

Formation minimale

Maîtrise

Expérience minimale

2+ ans

Langue de l’offre

anglais

Heures de travail

40 heures par semaine