Yahoo Mail is the ultimate consumer inbox with hundreds of millions of users. It’s the best way to access your email and stay organized from a computer, phone or tablet. With its beautiful design and lightning fast speed, Yahoo Mail makes reading, organizing, and sending emails easier than ever.

A Little About Us

Yahoo makes the world’s daily habits inspiring and entertaining. By creating highly personalized experiences for our users, we keep people connected to what matters most to them, across devices and around the world. Yahoo’s vast businesses span across Search, Communications, Media, and many other verticals.

 

Yahoo generates a huge amount of data every day and it is critical to collect, manage and process data at petabyte scale to provide timely and accurate insights to executives, sales, product managers and product developers on all aspects of user interaction. 

The Mail Analytics Engineering team at Yahoo is responsible for building mission critical data systems, pipelines, warehouses, analytics systems, and Machine Learning/AI/data mining programs for the Communications business. We are constantly pushing the envelope of data platforms due to the insane amount of data we need to harness. 

A Lot About You

As part of the Mail Analytics Engineering team, you will be working on data engineering pipelines and next generation Machine Learning- and AI-based data infrastructure, supporting new functionalities on existing platforms, and mining data for analytics insights and product features. 

Our Big Data footprints are among the largest few in the world, at double-digit petabyte scale. Developing this infrastructure presents many technical challenges in the areas of efficient query processing, large-scale stream processing, machine learning and modeling, as well as satisfying complex business rules.

If you are someone who is passionate about harnessing data at insane scale, enjoys working with new technologies, setting up petabyte data infrastructures and implementing new machine learning solutions and metrics systems, we want to hear from you!

Your Day

• Improve our existing data infrastructures for machine learning and deep learning using your core expertise

• Work with other engineers to implement algorithms and systems in an efficient way

• Take end to end ownership of Machine Learning-based distributed data systems - from data pipelines and training, to real time prediction engines.

• Develop complex queries, very large volume data pipelines, and analytics applications

• Develop complex queries and software programs to solve analytics and data mining problems

• Interact with data analysts, data scientists, product managers, and software engineers to understand business problems, technical requirements to deliver data solutions

• Prototype new metrics or data systems

• Lead data investigations to troubleshoot data issues that arise along the data pipelines

• Maintenance and improvement of released systems

• Engineering consulting on large and complex warehouse data

You Must Have

• BS/MS/PhD in Computer Science/Electrical Engineering, or related engineering disciplines, ideally with specialization in Data Engineering or Machine Learning

• Strong fundamentals: algorithms, distributed computing, data structure, database

• Fluency with: Python/Java/Scala/SQL

• 5+ years of industry experience on very large scale analytics or ML systems development

• 2+ years of experience with Google Cloud Platform (BiqQuery, Dataproc, Composer, Dataflow, BigTable, etc.)

• 2+ years of experience in Hadoop technologies (Map/Reduce, Pig, Hive, HBase, Spark, Kafka, Oozie, etc.)

• Experience in data modeling, schema design, ETL, and data analysis

• Self-driven, challenge-loving, detail oriented, teamwork spirit, excellent communication skills, ability to multitask and manage expectations

Preferred

• Experience with machine learning algorithms, NLP, and/or statistical methods a big plus

• Experience in any of: machine learning, analytics, data mining, or data mart and warehouse

• Experience with Deep Learning platforms (Tensorflow/Keras/Spark MLlib)

#LI-KO1

Yahoo is proud to be an equal opportunity workplace. All qualified applicants will receive consideration for employment without regard to, and will not be discriminated against based on age, race, gender, color, religion, national origin, sexual orientation, gender identity, veteran status, disability or any other protected category. Yahoo is dedicated to providing an accessible environment for all candidates during the application process and for employees during their employment. If you need accessibility assistance and/or a reasonable accommodation due to a disability, please submit a request via the Accommodation Request Form (www.yahooinc.com/careers/contact-us.html) or call 408-336-1409. Requests and calls received for non-disability related issues, such as following up on an application, will not receive a response.

At Yahoo, we know that diversity makes us stronger. We are committed to a collaborative, inclusive environment that encourages authenticity and fosters a sense of belonging. We strive for everyone to feel valued, connected, and empowered to reach their potential and contribute their best. Check out our diversity and inclusion (www.yahooinc.com/diversity/) page to learn more.

The compensation for this position ranges from $128,250.00 - $266,875.00/yr and will vary depending on factors such as your location, skills and experience. The compensation package may also include incentive compensation opportunities in the form of discretionary annual bonus or commissions, in addition to equity incentives. Yahoo provides industry-leading benefits including healthcare, 401K savings plan, company holidays, vacation, sick time, parental leave and an employee assistance program. Eligibility requirements apply.

Yahoo has a high degree of flexibility around employee location and hybrid working. In fact, our flexible-hybrid approach to work is one of the things our employees rave about. Most roles don’t require specific regular patterns of in-person office attendance. If you join Yahoo, you may be asked to attend (or travel to attend) on-site work sessions, team-building, or other in-person events. When these occur, you’ll be given notice to make arrangements. 

If you’re curious about how this factors into this role, please discuss with the recruiter.

Currently work for Yahoo? Please apply on our internal career site.