The Data Scientist will play a key role in expanding the MENA region's machine learning models and capabilities to the Turkish market. You will leverage your strong data science skills in statistics, modeling, and machine learning to identify opportunities to apply existing MENA models to the Turkish market, while also developing new models tailored to the unique needs and characteristics of the Turkish customer base. You will work closely with business stakeholders across the MENA and Turkey teams to understand requirements, gather and analyze data, build and optimize models, and deliver impactful data-driven solutions. This role requires both technical depth in data science as well as business acumen to drive successful model deployment and adoption. The ideal candidate will have excellent coding, analytical, and problem-solving skills, along with the ability to communicate complex technical concepts to non-technical stakeholders.
Key job responsibilities
As a Data Scientist, you will
* Analyze MENA region machine learning models and identify opportunities to adapt and apply them to the Turkish market. Collaborate with stakeholders in Turkey to understand the unique data and modeling requirements.
* Develop new machine learning models tailored to Turkish customer behaviors, preferences, and market dynamics. Deploy these models to deliver actionable insights and data-driven solutions.
* Collect, clean, and prepare data from various sources to build high-quality datasets for modeling. Employ best practices in data management, model development, and model validation.
* Communicate model performance, insights, and recommendations effectively to technical and non-technical stakeholders across the MENA and Turkey teams. Provide guidance on model implementation and adoption.
* Stay up-to-date on the latest machine learning techniques and technologies. Identify opportunities to innovate and improve the MENA-Turkey modeling capabilities over time.
- Bachelor's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science
- 2+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- Experience implementing algorithms using both toolkits and self-developed code
- Experience in at least one of the related science disciplines (optimization - LP, MIP, statistics, machine learning, process control, combinatorial optimization)