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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