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Company Sponsored Ads is one of the fastest growing business domains and we are looking for talented scientists to join this team of incredible scientists to contribute to this growth. We are still in Day 1 and there is an abundance of opportunities that are yet to be explored. We are a team of highly motivated and collaborative team of machine learning scientists, with an entrepreneurial spirit and bias for action. We have a broad mandate to experiment and innovate, and we are growing at an unprecedented rate with a seemingly endless range of new opportunities.
The Targeting and Recommendations team works across the entire spectrum of sponsored product ad serving including CTR prediction, dynamic pricing, ranking, ad relevance, ad quality, query understanding, recommendation systems, and much more. Our technology enables thousands of brands, vendors, sellers and authors to drive discovery and sales of their products across millions of customers. This role specifically sits within the broader Sponsored Products Marketplace team within Ads with the primary focus on building recommenders for advertisers for targeting, bidding and budgets.
We are looking for an Applied Scientist to build the next generation of recommendation services for advertisers. You will be expected to demonstrate strong ownership, and should be curious to learn and leverage textual, image, and query level data to help advertisers optimize their performance. This role specifically will focus on building recommenders for keywords, bids and budgets.
This role will challenge you to utilize cutting edge machine learning techniques in the domain of query understanding, natural language processing (NLP), deep learning, and image recognition to deliver significant impact for the business. The ideal candidates will be able to work cross functionally across multiple stakeholders, synthesize the science needs of our advertisers, develop models to solve business needs, and implement their solutions in production. Hence, we would expect them to be independent, have a natural bias to action, strong communication skills, and be agile to make continuous incremental progress on a project without losing focus of the end goal.
Use machine learning and analytical techniques to create scalable solutions for business problems
Work closely with software engineering and product teams across the organization to drive real-time model implementations and new feature creations
Work closely with business stakeholders to identify opportunities of current model improvements and new models to significantly benefit the business bottom-line.
Collaborate with scientists within the Ads organization as well as other parts of Company business to share and imbibe learnings that benefit our models.
Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation
Research and implement novel machine learning and statistical approaches.
A Masters Degree in Computer Science, Math, Statistics, Engineering, or related field.
3+ years of Applied Science experience in related industry.
3+ years of building machine learning models and helping bring those models to production.
Strong skills in statistics.
Proficient in at least one of the common programming languages, e.g., Python or Java.
Strong verbal and written communication skills.
PhD degree in Computer Science, Math, Statistics, Engineering, or related field.
Experience with delivering large scale solutions with tight latency constraints from research to final product implementation.
Experience working with customer facing problems.
Previous experience with search engines, digital ads, and/or machine learning platform is a plus.
Experience with at least one big data technology such as AWS, Apache Hadoop, Apache Spark, Apache Pig, Apache Hive, Apache Lucene/SOLR or Apache Storm/Samza.
Strong technical skills and experience with the latest ML frameworks.
Experience in building and maintaining mission-critical services.
Company is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation
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