Cien is an AI-first startup and we are global by design, with offices in Barcelona, Miami Beach, and Dallas. Our workforce is also an example of our vision, we are multicultural and diverse, and we pride ourselves on hiring the best people out there.
Our app provides a new way to measure and increase sales productivity. Using AI, the app connects the invisible dots in our customers’ sales data to predict outcomes, uncover improvement areas and recommend the biggest wins for their team.
The founding team members have all had major previous SaaS company successes, and at Cien we strive to make something 100 times better than before, hence the name! We aim to build the best workplace possible to support our employees -- through our benefits, workplace design, perks and culture.
We need great people like you to help us shape the future of sales strategy, all in the context of the Machine Learning field and with an international and diverse team.
We offer an exciting and innovative internship program in Data Science!
* Work alongside our Data Scientists to create models for predicting sales people’s behavior
* Create Data Visualizations
* Conduct data cleaning and detection of outliers in different sets of data using tools like MongoDB and Python etc.
The internship includes on-the-job training, collaboration with other team members, challenging work and a cool working environment.
If you like working on challenging and intriguing projects in an entrepreneurial environment that welcomes creative approaches and solutions and if you are familiar with Python, and have some experience in the Data Science world, then our internship is the right next step for your career.
We are looking for masters students, currently enrolled in Spanish universities, with advanced written and verbal communication skills in English and available to work for 25 hours a week in our office in Barcelona.
Interested? Apply now!
Cien is an equal opportunity employer and value diversity in our company. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, veteran status, or disability status.