Senior Applied Scientist, MENA Stores
3 weeks ago
We are seeking a highly skilled Senior Applied Scientist to join our MENA Science team and drive the development of cutting-edge machine learning solutions for our customers in the MENA region.
As a Senior Applied Scientist, you will leverage your expertise in machine learning and data science to create innovative solutions that directly address critical customer problems.
Key Responsibilities- Design, develop, evaluate, deploy, and update data-driven models and analytical solutions for machine learning (ML) and/or natural language (NL) applications.
- Develop and/or apply statistical modeling techniques, optimization methods, and other ML techniques to different applications in business and engineering.
- Invent, implement, and deploy cutting-edge machine learning algorithms and models to solve complex, real-world problems for our MENA customers.
- Collaborate closely with cross-functional teams, including product managers, engineers, and other applied scientists, to identify high-impact areas for innovation.
- Prototype and test new approaches, such as leveraging large language models (LLMs) and other advanced techniques, to drive measurable improvements in key business metrics.
- Stay up-to-date with the latest advancements in machine learning and data science, and proactively identify opportunities to apply these techniques to drive business impact.
- Contribute to the broader scientific community by publishing your work at top-tier conferences and journals.
The MENA Science team works closely with the business and engineering teams in building ML solutions that create an impact for MENA businesses.
This is a great opportunity to leverage your machine learning and data mining skills to create a direct impact on consumers and end users.
Requirements- PhD, or Master's degree and 5+ years of building machine learning models for business application experience.
- Experience programming in Java, C++, Python or related language.
- Expertise in one of the applied science disciplines, such as machine learning, natural language processing, computer vision, or deep learning.
- Understanding of basic data structures, algorithms, model evaluation techniques, performance, and optimality trade-offs.
- Proficient in any two of these areas: large language models, NLP (Information retrieval, Machine Translation), Computer Vision, Classification models using Boosting/Bagging or Deep Neural Networks.
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