The story of Yıldız Holding, which started with biscuit production in Istanbul in 1944, continues today with our food-snack products that we have reached 4 billion people in 5 continents with more than 300 brands and with our retail companies all over Turkey. With our 80 thousand employees, the majority of whom are located in Turkey, we aim to reach the better without stopping, and we produce a wide range of products from biscuits to chocolate, from frozen food to packaging in a total of 45 factories, 20 of which are abroad. We always raise the bar in economic contribution, employment, exports, social solidarity and sustainability. We give priority to social contribution with the principle of "Make Happy Be Happy" and we have been producing happiness for more than 80 years with our products, services and sustainable social responsibility understanding.

Our company Yıldız Tech, established to support the software development journeys of our digital applications within our group and to create innovative solutions, aims to enable our customers operating in the e-commerce sector to make the most of next-generation technologies, achieve success through digital and analytical solutions, and capitalize on emerging opportunities to attain sustainable benefits.

Job Description

Yıldız Tech's Digital Transformation organization is seeking a Data Scientist / Senior Data Scientist to shape the vision, define the strategy, and drive the execution of our data-driven initiatives. In this role, you will understand user needs and business objectives, facilitate the development of data models and analytics solutions, and support data-driven decision-making processes.

What Awaits You, What Will Be Your Responsibilities?

• Researching, designing, implementing, and evaluating machine learning approaches and models.
• Assisting in analyzing large datasets using statistical techniques and machine learning algorithms.
• Supporting the development, implementation, and evaluation of predictive models and data-driven solutions to address business challenges.
• Preprocessing and cleaning raw data to ensure its quality, integrity, and usability for analysis.
• Applying data wrangling techniques to handle missing values, outliers, and inconsistencies in the data.
• Creating visualizations, charts, and dashboards to communicate insights and findings from data analysis effectively.
• Collaborating with senior data scientists, analysts, and business stakeholders to understand project requirements and objectives.
• Contributing ideas and insights to team discussions and brainstorming sessions.
• Staying updated on the latest trends, tools, and techniques in data science and machine learning.
• Documenting analysis methods, findings, and results in clear and concise reports.
• Preparing presentations and documentation to communicate project outcomes to stakeholders and team members.
• Deploying machine learning models into production environments using containerization, orchestration, and model serving frameworks.
• Exploring, fine-tuning, and applying Large Language Models (LLMs) and agentic AI solutions to address business needs and automation opportunities.

What will be the qualifications we expect from you?

• BS Degree in Statistics, Computer Science/Engineering, Industrial Engineering (or other related engineering fields).
• Good command of SQL.
• Strong programming and scripting skills in Python (packages: pandas, NumPy, matplotlib, scikit-learn, TensorFlow, PySpark, etc.).
• Minimum 3 / 5 years of experience in related fields.
• Hands-on project experience in some of the following areas:
• Predictive analytics: cross-sell/up-sell modelling, churn prediction, demand forecasting, time series analysis.
• Customer analytics: segmentation, recommendation systems.
• AI and machine learning applications: image processing, natural language processing (NLP).
• Excellent command of English.
• Ability to manage a variety of cross-organizational projects (scope, stakeholders, desired outcomes), working closely with a broad range of internal and external teams.
• Effective communication skills.
• Analytical perspective.

The following qualifications are a plus:

• Understanding and hands-on experience with Large Language Models (LLMs) and agentic AI frameworks, including fine-tuning, embedding models, prompt engineering, or agent orchestration (e.g., LangChain, OpenAI APIs, Hugging Face Transformers).
• Hands-on experience in deploying machine learning models using tools such as Docker, Kubernetes, and CI/CD pipelines (e.g., Jenkins, GitLab CI).
• Familiarity with model serving frameworks such as MLflow, FastAPI, or TorchServe.
• Practical experience with cloud platforms such as AWS and/or Azure, especially in infrastructure management, data storage, networking, and resource provisioning (e.g., S3, Blob Storage, EC2, VMs, IAM).

Which skills will highlight you?

• Strong problem-solving and analytical thinking skills.
• Effective communication and collaboration abilities.
• Ability to manage and prioritize multiple projects and tasks simultaneously.
• Hands-on experience in deploying machine learning models into production environments.
• Curiosity and practical experience with Large Language Models (LLMs) and agentic AI frameworks.
• Team spirit and leadership in collaborative environments.
• Proficiency in MS Office applications.

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