Data Scientist

Responsabilitites

• As a Data Scientist on our Performance Marketing team, you will be the driving force behind the analysis and optimization of our digital campaigns;
• You will translate complex data into actionable insights and contribute directly to our company's growth; 
• In-depth Analysis: Analyze and interpret extensive data from our performance marketing channels (e.g., Google Ads, Meta Ads, LinkedIn Ads, SEO) with a focus on KPIs like CPA, ROAS, and conversion rates;
• Predictive Modeling: Develop and implement machine learning models to optimize the performance of our marketing channels;
• Attribution Modeling: Validate advanced multi-touch attribution models to determine the true value of each  marketing channel;
• Optimization & Automation: Develop algorithms to optimize bidding strategies, budget allocation, and target audience segmentation; 
• Testing & Validation: Take responsibility for the design, execution, and statistical evaluation of A/B and multivariate tests to continuously improve campaign performance; 
• Visualization & Reporting: Create insightful dashboards (e.g., in Tableau, Power BI, or Google Data Studio) and reports that enable the marketing team and management to make data-driven decisions; 
• Collaboration: Work closely with Performance Marketing Managers to formulate hypotheses, design experiments, and derive data-driven strategies.

Requirements

• Education: A successfully completed degree in Computer Science, Statistics, Mathematics, Business Informatics, or a similar quantitative field; 
• Experience: At least 2-3 years of professional experience in a data science role, ideally with a proven track record in e-commerce, digital marketing, or AdTech; 
• Technical Skills: Excellent programming skills in Python and proficiency with relevant data science libraries (e.g., Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch); 
• Expert knowledge of SQL and experience with relational databases and data warehouses (BigQuery preferred); 
• Experience with data visualization tools such as Tableau or Looker Studio; 
• Knowledge of cloud environments (GCP preferred); 
• Methodological Expertise: A solid understanding of statistical methods, experimental design (A/B testing), and common machine learning algorithms (regression, classification, clustering);
• Soft Skills: A strong analytical and solution-oriented mindset. You have the ability to communicate complex technical concepts clearly and persuasively to a non-technical audience. You are proactive, a team player, and have a keen interest in the business context behind your analyses; 
• Languages: Fluency in English (written and spoken)