Data Scientist

About Qualysoft ·        25 years of experience in software engineering, established in Vienna, Austria·        Active in Romania since 2007, with office in central Bucharest (Bd. Iancu de Hunedoara 54B)·        Delivering End to End IT Consulting Services  - From Team Augmentation and Dedicated Teams to Custom Software Development  ·        We deliver scalable enterprise systems, intelligent automation frameworks, and digital transformation platforms·        Cross-industry experience by sustaining global players in BSFI (Banking, financial services and insurance), Telecom,Retail & E-commerce, Energy and Utilities, Automotive, Manufacturing, Logitics, High Tech·        Global Presence: Switzerland, Germany, Austria, Sweden, Hungary, Slovakia, Serbia, Romania, and Indonesia·        International team of 500+ software engineers·        Strategic partnerships: Microsoft Cloud Certified Partner, Tricentis Solutions Partner in Test Automation and Test Management, Creatio Exclusive Partner, Doxee Implementation Partner·        Powered by cutting-edge technologies: AI, Data & Analytics, Cloud, DevOps, IoT, and Test Automation.·        Project beneficiaries ranging from large-scale enterprises to startups·        Stable growth and revenue increase year over year, a resilient organisation in volatile IT market conditions·        Quality-first mindset, culture of innovation, and long-term client partnerships·        Global and local reach – trusted by key industry players in Europe and the US 

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)

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