Principal Applied Scientist- Feeds and AI

8 Months ago • 5 Years +

Job Description

Microsoft's Feeds and AI team seeks a Principal Applied Scientist to enhance recommendation algorithms within their content ecosystem (MSN, Microsoft Start). Responsibilities include algorithm development and optimization using machine learning techniques, including generative AI, to improve content quality and user engagement. Data analysis, modeling, and collaboration with cross-functional teams are key. The ideal candidate possesses a Master's degree in a relevant field (Computer Science, Statistics, Data Science), 5+ years of experience in recommender systems, strong programming skills (Python, C# a plus), and expertise in NLP and LLMs. The role involves building and enhancing algorithms to drive product features and user engagement, analyzing performance metrics, and incorporating user feedback.
Good To Have:
  • Experience with C#, C++
  • Experience with generative AI/LLMs
  • Experience in search engine or online advertising
Must Have:
  • Master's degree in relevant field
  • 5+ years experience in recommender systems
  • Strong Python programming skills
  • Expertise in machine learning & AI
  • Excellent problem-solving skills
Perks:
  • Industry leading healthcare
  • Educational resources
  • Discounts on products and services
  • Savings and investments
  • Maternity and paternity leave
  • Generous time away
  • Giving programs
  • Networking opportunities

Add these skills to join the top 1% applicants for this job

algorithms
python
data-science
data-analytics
user-experience-ux
innovation
cross-functional
performance-analysis
team-management

Overview

In Feeds and AI team, we’re building MSN, a content powerhouse for every person on the planet to be informed, entertained, and inspired. Microsoft Start is the place for all to read, watch, listen, create, connect with people of shared interests, and experience wonders in the world.

 

We are looking for a skilled and experienced Principal Applied Scientist to join our team. As Principal Applied Scientist focusing on recommender systems, you will play an important role in enhancing and optimizing our recommendation algorithms within our content ecosystem to achieve product and business growth goals.

Qualifications

  • Master's degree in Computer Science, Statistics, Data Science, or related field, with solid background in machine learning, data mining or related applied science.
  • 5 years of work experience in recommender systems, search engine, or online advertising, with rich experience on machine learning algorithms, generative AI / LLMs, statistics, data mining techniques, and their application on personalization.
  • Excellent problem-solving skills and ability to work in a fast-paced, collaborative environment. Strong communication and teamwork skills, with the ability to effectively present and explain technical concepts to diverse audiences.
  • Strong programming skills in Python and experience with other programming languages like C#, C++ is a plus.

 

Responsibilities

 

  • Algorithm Development and Enhancement for Content Quality in News & Feeds
    • Work with cross-functional teams to design, develop, and implement recommendation algorithms to deliver product features and drive user engagement.- Optimize existing recommendation algorithms by analyzing performance metrics and user feedback, incorporating advanced machine learning techniques including generative AI techniques.
  • Innovation in the area of NLP, LLM, and recommender system.
  • Data Analysis and Modeling
    • Perform data analysis to identify patterns, trends, and opportunities to improve the relevance and quality of our recommendation systems.
    • Build systemic solutions and models to optimize user experience.
Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.
Industry leading healthcare
Educational resources
Discounts on products and services
Savings and investments
Maternity and paternity leave
Generous time away
Giving programs
Opportunities to network and connect

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