Data Scientist

Data Scientist The Hague, NL - Engineering

Bachelor’s or Master’s degree in Statistics, Mathematics, Computer Science, or another quantitative field. Experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights from large data sets. Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks. Excellent written and verbal communication skills for coordinating across teams. Personality Opportunity to work in a cutting-edge tech scale-up with a talented team. A collaborative environment that fosters innovation and professional growth. Competitive salary and comprehensive benefits. Employee Stock Options (optional).

Perks Opportunity to work in a cutting-edge tech scale-up with a talented team. A collaborative environment that fosters innovation and professional growth. Competitive salary and comprehensive benefits. Employee Stock Options (optional) How to apply? At Beatgrid, we believe that the power of our cross-media solutions resides in the happiness and wellbeing of our team. The success of our business growth is a direct consequence of having a healthy corporate culture. We are on the path to becoming the future of cross-media measurement, but this is only achievable when blending a passion for work with life enjoyment. We are always looking for world-class talent, ready to tackle new daily ambitious challenges that will ultimately shape the future of cross-media measurement. (Please refrain from applying if you don’t have a valid VISA to work in the Netherlands).

We are looking for a skilled Data Scientist to join our team. The Data Scientist will interpret and manage the data we collect and use. Analysis, problem-solving, and communication skills are essential, as well as collaboration with the Data Engineer and other team members.

Responsibilities​ Data Analysis and Modeling: Develop custom data models and algorithms to apply to data sets Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting, and other business outcomes. Advanced-Data Interpretation: Assess the effectiveness and accuracy of new data sources and data-gathering techniques. Develop A/B testing framework and test model quality. Cross-functional Collaboration: Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions. Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques, and business strategies.