Senior Applied Scientist
Job Description
Join the Microsoft Shopping team! We deliver smart shopping experiences with personalization, savings, transparency, and convenience, ensuring confidence in every purchase. Microsoft Shopping is your personal shopping companion, empowering customers to shop smarter and discover what they love. By harnessing the power of AI (artificial intelligence), LLMs (large language models) and LLM-based Agents, we are building best-in-class shopping experiences across Bing, MSN, and Edge. If you are passionate about transforming the online shopping experience for millions of users, this role is for you.We are seeking a Senior Applied Scientist who is passionate about machine learning, data analysis, and ML (machine learning) modeling to join our team. Your expertise will drive innovation and ensure the team is aligned with the Microsoft Shopping vision. This position offers a unique blend of scientific research, innovation, and strategic influence, allowing you to make a significant impact on both the team and the overall shopping experience at Microsoft Shopping.Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
Locations
- Cairo, Cairo, Egypt, Cairo, Cairo, Egypt
Salary
Salary not disclosed
Estimated Salary Rangemedium confidence
120,000 - 180,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Required Qualifications
- Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research) OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR equivalent experience. (degree)
- OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) (degree)
- OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) (degree)
- OR equivalent experience. (degree)
- 3+ years of industry experiences in machine learning or Natural Language Processing. (degree)
- Experience with LLMs (prompting, fine tuning, deployment). (degree)
- Experience with coding including programming language, including, but not limited to, Python, C, C++, C#, Java, JavaScript. (degree)
- Demonstrated ability to be productive and effective in a highly collaborative environment. (degree)
- Experience in Big Data machine learning with Cosmos/Scope/Spark/. (degree)
- Experience with design, problem solving, and data analysis skills, with demonstrated passion for quality, performance, and engineering excellence. (degree)
Preferred Qualifications
- Demonstrated ability to be productive and effective in a highly collaborative environment. (degree)
- Experience in Big Data machine learning with Cosmos/Scope/Spark/. (degree)
- Experience with design, problem solving, and data analysis skills, with demonstrated passion for quality, performance, and engineering excellence. (degree)
Responsibilities
- Leverage state-of-art machine learning techniques to provide best personalized experience to end users.
- Originate, implement, and iterate on machine learning features & models to keep improving our product quality.
- Closely collaborate with different teams within Microsoft to expose best personalized contents to end users, enable agile development & experiments, deliver cross-team impact.
- Team lead and mentor resources across projects.
Travel Requirements
4 days / week in-office
