Job Site Test - Lever Middleware Test Company : Job Details

ABOUT THE TEAM

Trendyol Go, originally founded as the instant delivery arm of Trendyol, one of Turkey's leading e-commerce platforms, was acquired by Uber to join forces in accelerating the future of local commerce and on-demand delivery. Born from a dynamic startup spirit and backed by Trendyol, Trendyol Go connects local merchants, couriers, and customers in real time to meet everyday needs with speed and reliability.

Our on-demand platform offers instant delivery for food, groceries, and more, bringing convenience and choice right to the doorsteps of millions. As part of Uber, the world's largest mobility and delivery technology platform, we combine local market expertise with cutting-edge technology to redefine urban delivery.

We are committed to powering seamless experiences that enable customers to get what they want, when they want it, while creating flexible earning opportunities for couriers. With a mission to strengthen local commerce and foster positive impact on merchants and couriers, Trendyol Go is evolving rapidly, expanding its offerings and reach, innovating with technology, and delivering exceptional service every step of the way.

YOUR MAIN RESPONSIBILITIES

TGO's Data Science Team consists of talented professionals responsible for all Data Science related aspects of TGO and beyond.

You will work on cutting-edge algorithms to enhance the customer and seller experience in the real-time delivery space.

Your work will involve improving personalization and recommendation models, optimizing search and ranking systems, and ensuring high relevance.

Be a champion of data-driven decision-making and algorithmic thinking within TGO.

Build, deploy, and continuously improve ML models that solve real-world business problems.

Design comprehensive ML pipelines, often combining multiple algorithmic approaches.

Execute A/B tests, interpret statistical results, and iterate based on learnings.

Translate business requirements into technical solutions and communicate insights effectively across teams.

Ensure all models are aligned with business goals and deliver measurable value.

Stay updated with the latest data science advancements and bring new ideas to the table.

Collaborate with stakeholders across the organization to identify opportunities to leverage data for strategic outcomes.

WHAT WE ARE LOOKING FOR

Bachelor's or Master's degree in Industrial Engineering, Computer Science, Statistics, or a related field. Minimum 2 years of experience in machine learning (classification, regression, ranking, clustering, deep learning, etc.). Proficiency in Python and SQL; hands-on experience in ML pipeline design is a must. Familiarity with ML libraries like scikit-learn, PyTorch, or TensorFlow is a plus. Strong skills in data mining and statistical analysis. Experience in NLP techniques and Generative AI is a plus. Ability to clearly explain complex data concepts to both technical and non-technical audiences. High sense of ownership and urgency in a fast-paced, evolving environment. Excellent command of English, both written and verbal. Experience in local commerce (especially in real-time delivery) or e-commerce is highly valued.

JOIN US AND

* Take ownership from day one and grow your skills in a collaborative, international environment.

* Experience a start-up spirit with the stability of a large tech company.

* Tackle impactful challenges in local commerce using agile practices.

* Be part of a creative, focused team that values collaboration and results.

* Access a rich learning platform for ongoing personal and professional development.

* Work with global experts, supported by mentoring and upskilling opportunities.

* Advance based on talent and impact — not just job titles.

* Stay connected through engaging team events, meetings, and social activities.

* Enjoy top-tier benefits.

* Balance flexibility and team bonding through our hybrid work model, including summer remote work opportunities.

We look forward to your application! We operate on a hybrid model, combining the efficiency of remote work with the collaboration of in-person teamwork. Teams come together on designated days to foster creativity and connection. Note: Hybrid work applies only to hybrid roles. Some positions may require regular on-site presence.