Key Responsibilities

• Analyze and interpret complex datasets;

• Explore, clean, and analyze structured data to identify trends, patterns, and opportunities that support business and product decisions;

• Develop analytical and statistical models;

• Build and apply statistical models, forecasting approaches, 
and analytical frameworks to answer business questions and 
evaluate performance ;

• Design and track business metrics ;

• Define, calculate, and monitor key business and product metrics such as revenue, growth, retention, engagement, and conversion ;

• Design ana analyze experiments (e.g: A/B tests), evaluate results, and provide clear recommendations based on data ;

• Translate business questions into analytical solutions ;

• Work closely with stakeholders to understand goals and challenges, and convert them into well-defined analytical tasks and insights ;

• Validate data sources, assumptions, and results to ensure accuracy, reliability, and trust in analytical outputs ;

• Collaborate across teams ;

• Partner with product, marketing, analytics, and engineering teams 
to align data insights with business priorities.

Required Qualifications

• Experience in data analysis/data science roles ;

• Solid understanding of statistics, probability, and applied data analysis ;

• Familiarity with forecasting, time-series analysis, or customer analytics ;

• Proficiency in SQL for data querying and analysis ;

• Proficiency in Python for data analysis, modeling, and visualization ;

• Familiarity with concepts such as supervised/unsupervised machine learning, clustering algorithms, multiple linear regression ;

• Experience working with analytical datasets in cloud-based data warehouses ;

• Ability to design meaningful metrics and interpret them in a business context ;

• Strong analytical thinking and problem-solving skills ;

• Excellent communication skills and ability to explain complex findings clearly ;

• Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, or a related field ;

• English level: B2 or higher.

Nice to Have

• Experience with business intelligence and data visualization tools (e.g. Power BI, Tableau, Looker)

• Experience working with marketing, product, or customer data ;

• Experience with big data.

What We Offer

• Opportunity to work on real-world data science problems with direct business impact ;

• Continuous learning and professional development opportunities.