Data & Analytics Intern - Istanbul, Turkey

Are you ready to explore PepsiCo and be part of this iconic multinational?

PepsiCo's strength is its people. Around the world, we're working hard to give people the tastes they crave and the nutrition they need. We dream globally and act locally, constantly innovating to sustain our planet, our people, our communities, and our business practices for winning together. We are committed to Performance with Purpose; pushing to be best and fully committed to the people we share the planet with.

Seize the day for real life on the job Learning? Enjoy some flexibility that will ensure you are balancing your personal and professional life?

Our employees are at the heart of PepsiCo. Through the Company's dedication to Talent Sustainability, we continue to support the development of employees.

We are looking for a Data & Analytics Intern to join our IT team in Istanbul. Directly report to Analytics Manager.

A Space to Be You

PepsiCo is an equal opportunity employer. We are committed to providing an accessible, inclusive, open and welcoming workplace environment for people with different abilities, backgrounds, lifestyles, sexual orientation, gender identity, needs and expectations, helping all individuals to make the most of their professional potential.

• Maintain current analytics tools by improving algorithm, documenting scripts and creating descriptive reports and dashboards
• Closely monitor market trends and internal sales data to evaluate analytic tool outputs and model performance
• Test new algorithms to evaluate model improvement opportunities
• Partner with the data science team (local & Europe hub) to assess and deliver analytical solutions.

• Senior year university student, master's student, or recent graduate.
• Excellent verbal and written communication skills in both English and Turkish.
• Experience in managing projects using data, understanding, and analytics.
• Ability to comprehend complex business requirements and communicate analytical outputs to stakeholders. Experience with Machine Learning, AutoML, and non-linear regression models.
• Understanding of the ETL process.
• Experience with data and analytics tools such as Excel, SQL, R, Python, Jupyter notebooks, PowerBI