About Taager
Taager is the first B2B startup focused on social sellers- Merchants. We are democratizing the social e-commerce space by enabling budding and seasoned entrepreneurs to sell online with no required capital, inventory, or operational experience. Our merchants are covered in merchandising, warehousing, shipping, cash collection, and customer service.

In 2019, we started as a team of 8 people. Now we have over 350 employees across Egypt, KSA, and the UAE. We serve more than 34K social e-commerce sellers from incredibly diverse backgrounds – from students earning a part-time income to highly ambitious digital marketing experts looking to become solo entrepreneurs. The sellers on our platform benefit from access to 2,500+ highly marketable products. Our people are driven by our mission and desire to deliver the most seamless customer experience to the sellers on our platform. With a continuous focus on quality and execution, we are changing the social e-commerce landscape in the MENA region!

Our Mission

Our mission is to empower anyone to start and scale their e-commerce business.

Our Vision

We envision a world where everyone can sell online, make a living, and even get rich in an easy, low-risk environment. A world where the magic of technology becomes accessible to the most talented Merchants.

Why Taager?

• You'll be working with a diverse team based in different countries around the globe
• Unlimited vacations.
• We offer a comprehensive compensation package (Salary + Stock Options + Biannual Salary Increases), as we believe our employees should be compensated fairly for their talent and capabilities.
• You will be working alongside talented, caring, and ambitious individuals. We're very intentional about our selection process so that we hire people who can help us become a vibrant and healthy work environment for everyone.
• We offer a comprehensive medical insurance package.
  
  

About the Role

We are looking for a detail-oriented data analyst that has an eye for discovery and digging out associations. As part of the data team, you will be crucial in extracting insights from data to drive business decisions, optimize operations, and enhance customer experiences.

Responsibilities:

• Work closely with stakeholders across engineering, product, and UX teams to drive product decisions.
• Manipulate and translate big data into key insights to assist the development of relevant, impactful, and measurable actions.
• Design experiments and A/B testing will enable feature teams to make effective product decisions and help teams evaluate the results of these experiments.
• Build dynamic dashboards and visual aids to monitor platform activity and performance.
• Collaborate closely with product teams to understand and implement data requirements.
• Create data-driven product solutions for the product team leveraging shallow machine learning models.

Required skills :

• Proficiency in SQL for querying large datasets.
• Expertise in Python for data analysis and manipulation.
• Strong understanding of experimental design, statistical significance, and hypothesis testing.
• Experience designing and analyzing A/B tests.
• Strong foundation in statistics, including probability, distributions, and inferential statistics.
• Knowledge of shallow machine learning models (e.g., linear regression, logistic regression, k-means) and familiarity with machine learning libraries.
• Proficiency in visualization tools (e.g., Tableau) and building dynamic dashboards.
• Familiarity with cloud platforms (e.g., AWS, GCP).
• Ability to translate complex data into actionable insights and recommendations.
• Aptitude for identifying key issues and developing data-driven solutions.
• Excellent verbal and written communication skills to effectively convey complex data insights to non-technical stakeholders.
• Knowledge of product management and user experience principles to align data insights with business goals.

Preferred skills:

• Experience with DBT and Airflow.
• Experience with ETL processes and data pipeline development.
• Experience with data warehousing solutions (e.g., Snowflake).
• Understanding of containerization technologies (e.g., Docker, Kubernetes).
• Experience in the e-commerce industry.
• Experience building customer segmentation.