Master's degree in machine learning, mathematics, computer science, or related field
Hands-on experience developing and applying data-driven solutions in corporate or consulting settings
Strong knowledge of data processing, data modeling, algorithms, and data architecture
Intellectual curiosity and strong problem-solving skills
Preferred experience
Consumer marketing experience
Experience in the web industry
Qualification wording
A Master’s degree in machine learning, mathematics, computer science, or related fields
Hands-on experience developing and applying data-driven solutions in a corporate or consulting setting
Strong knowledge of data processing, data modeling, algorithms, and data architecture
Intellectual curiosity and excellent problem-solving skills
preferably in a consumer marketing context
experience in the web industry is a plus
Education & alternatives
What are we looking for?
- A Master’s degree in machine learning, mathematics, computer science, or related fields
- Hands-on experience developing and applying data-driven solutions in a corporate or consulting setting, preferably in a consumer marketing context (experience in the web industry is a plus)
Complete your application on job-boards.greenhouse.io. The employer’s form will show what is required.
Applying through Greenhouse
No account needed: the form is one page, with an “Autofill my application” option that reads your resume.
Greenhouse doesn’t read resumes over 2.5 MB, or details placed in a header, footer, text box, table or second column. The file still attaches, but a recruiter has to type you in by hand.
New Data Scientist postings at the employers we follow are down 3% over the last 5 weeks compared with the 5 before.
August 17Last week
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
Artefact is a new generation of data service providers, specialising in data consulting and data-driven digital marketing. It is dedicated to transforming data into business impact across the entire value chain of organisations. We are proud to say we’re enjoying skyrocketing growth.
The backbone of our consulting missions, today our Data consulting team has more than 400 consultants covering all Artefact's offers (and more): data marketing, data governance, strategy consulting, product owner…
What will you be doing?
Securing delivery on your projectsCommunicating your work and achievements among the teamWorking closely with your Consulting counterpart to build and maintain strong relationships with your clients and best understand their needsEnsuring that your solutions are bringing values to the client problematicBeing a good team player, knowing your role and responsibility in the global ambition
What are we looking for?
A Master’s degree in machine learning, mathematics, computer science, or related fields
Hands-on experience developing and applying data-driven solutions in a corporate or consulting setting, preferably in a consumer marketing context (experience in the web industry is a plus)
Strong knowledge of data processing, data modeling, algorithms, and data architecture
Intellectual curiosity and excellent problem-solving skills, including the ability to structure and prioritise an approach for maximum impact
Artefact is the place to be: come and build the future of data and marketing! Innovation: We have a passion for creating impacting projects and believe innovation can come from anyone.
Action: We make things rather than telling people how to make them.Collaboration: We believe in bringing talented people together, winning together, and in learning from each other.