Role overview
Who We Are
Artefact is a leading global consulting company dedicated to accelerating the adoption of data and AI to positively impact people and organizations. We specialize in data transformation and data marketing to drive tangible business results across the entire enterprise value chain.
Artefact offers the most comprehensive set of data-driven solutions per industry, built on deep data science and cutting-edge AI technologies, delivering AI projects at scale in all industry sectors. From strategy to operations, we offer an end-to-end approach and solutions: data strategy, data quality and governance, data platforms, AI Factory, data-driven customer experience and marketing ROI.
Our 2000+ employees operate in 27 countries (Europe, Asia, Americas, Middle East, Africa) and we partner with 1000 clients, including some of the world's top 300 brands such as Samsung, L'Oréal and Sanofi.
What you'll work on
- Real-World Impact: Deliver impactful projects by developing end-to-end machine learning pipelines to solve real-world problems across various industries.
- Collaborative Solutions: Work in feature teams alongside other data scientists, ML engineers, data engineers, software engineers, and product owners to build complex solutions.
- Software Engineering Improvement: Enhance your software engineering skills by applying ML Ops best practices while working with machine learning teams.
- Expertise Development: Become an expert in one of our data science practices: Time Series Forecasting, MLOps, NLP, Computer Vision, Optimization, or Customer Intelligence.
- Algorithm Discovery: Discover state-of-the-art algorithms and test them on real-world data during client projects.
What we're looking for
We're seeking someone who has:
- Educational Background: A completed Master's degree in a relevant field (e.g., computer science, machine learning, mathematics, or related subjects).
- Hands-On Experience: 1-3 years of experience in data science, analytics, or consulting, preferably within a marketing or digital context.
- Technical Skills: Strong knowledge of data processing, algorithms, and data architecture, along with proficiency in tools like Python, SQL, and R.
- Analytical Mindset: A passion for working with data to derive actionable insights and solve complex problems.
- Communication Skills: Excellent verbal and written communication skills, with the ability to discuss both technical and non-technical topics with clients and team members.
- Curiosity and Passion: A genuine interest in continuous learning and exploring new technologies and tools in data and AI.