QUALIFICATIONS AND JOB DESCRIPTION
As you know a brand gets all its power from its employees first. Then it becomes a big family together with its customers and it gets stronger. We, Hepsiburada, are the most powerful family in online shopping in Turkey since 2001. In 30 product categories with over 12.7 million products, we all not only make e-commerce to be loved by the Turkish people but also we make it indispensable. We received numerous awards, we set unreachable records, and we reached legendary success. We were granted "Turkey's Most Popular Brand" award in 2011, 2012, 2013 and we were chosen "E-commerce Site of the Year” in 2013. Achieving these successes could be possible with our family, that is, our employees and our customers.
Would you also like to join our family to become more powerful, to develop our service understanding and to make a difference?
Remember, #gelecekburada!
Join HepsiBurada’s Data Science team to work on big data and analytic challenges. In our Data Science team, we are looking for a data scientist who will be dedicated to our “Search” domain. In this role :
- You will work machine learning algorithms and statistical techniques on our big data platform using Hive, Python, Spark, Keras, TensorFlow or your open source tool of choice, to harness volumes of online/offline data at scale to tackle diverse search engine problems mainly on query understanding, search ranking, and search engine performance measurement.
- You will have the privilege to be the member of both Hepsiburada Data Science team and Search Development team. You will work closely with data scientists, software developers, QA engineers, business analysts and product owners.
The following background, competencies, experience, academic and personal attributes represent general guidelines for what the position requires:
- Strong business acumen and problem defining abilities to find the most efficient route going to optimal business solution
- Strong communication and data presentation skills
- Experiences of solving Natural Language Processing problems via deep learning or other machine learning algorithms.
- Hands-on application experience of machine learning models, statistical methods and optimization algorithms in real-life problems
- Feature engineering, feature selection and model validation abilities
- Strong theoretical background in machine learning algorithms such as multiple regression, logistic regression, k-means clustering, feedforward neural networks and sequence models.
- Strong programming, prototyping and scripting skills in Python, Hive and in at least one deep learning framework such as Keras, PyTorch or Tensorflow
- Experimental design and testing abilities
- Advanced academic degree (MS / PhD) typically in a quantitative discipline or related field is a plus
