Machine Learning Scientist III (Paid Apps Team)

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Machine Learning Scientist III - Paid App, Social, and New Channels

Are you passionate about pushing the boundaries of machine learning in a high-growth environment? If you excel in dynamic, collaborative settings and have a strong interest in applying machine learning and data science to glean actionable insights, Expedia's Paid App team has a compelling opportunity for you. As a Machine Learning Scientist III, you'll lead impactful projects, shaping the future of Paid App Data-driven Products and Applications with practical machine learning and deep learning approaches.

At Expedia, we leverage the power of data to drive innovation and enhance user engagement. Our Paid App team operates at the forefront of the dynamic business landscape, focused on continuous testing, learning, and delivering high returns on investments. If you thrive in a collaborative, rewarding, and dynamic learning environment and are eager to deepen your expertise in machine learning, a significant opportunity within the Paid App Data Science team awaits.

As a seasoned Machine Learning Scientist III, you'll be a senior leader driving advancements in machine learning and deep learning methods, applying your expertise to real-world data with excellent tech mentorship. Your responsibilities include developing end-to-end scalable machine-learning-based solutions that significantly impact revenue. Serving as the resident expert on machine learning methods, you will drive algorithmic performance, develop and improve content optimization models, and influence senior leadership for positive outcomes, steering the channel towards improved revenue, reduced costs, increased customer engagement, and enhanced brand value.

What you'll do:

• Lead the evolution of bidding algorithms, ads content optimization, and optimize capital allocation for paid app, social, and new channels, employing advanced machine learning techniques

• Develop cutting-edge, end-to-end data-driven solutions using a diverse range of machine learning approaches, including supervised, unsupervised, clustering, NLP, computer vision, and ranking

• Innovate image ranking solutions for dynamic ad campaign performance enhancement

• Combine NLP and computer vision to develop state-of-the-art catalog optimization models

• Create anomaly detection models through ensembling various simple and sophisticated models

• Utilize statistical methods for data-driven decision-making and manipulate large datasets for business insights

• Communicate complex analytical topics to multiple partners and senior leadership, fostering cross-functional collaboration

• Lead testing and experimentation, employing cutting-edge machine learning techniques to enhance overall performance

Who you are:

• Minimum 4 years of relevant work experience in applied machine learning and deep learning

• Master’s or PhD degree in Computer Science, Statistics, Economics, Engineering, Applied Mathematics or related quantitative field; or equivalent related professional experience

• Strong object-oriented programming skills in Python (hands-on experience is a must) and in ML and Deep learning Python libraries

• Expertise in advanced machine learning techniques, including deep learning, data mining, clustering, regression models, predictive modeling, optimization, and ranking

• Familiarity with different testing methods (A/B OLS regression, t-test, Bayesian testing, Difference in Difference testing, look-alike testing, etc.)

The total cash range for this position in Seattle is $137,500.00 to $192,500.00. Employees in this role have the potential to increase their pay up to $220,000.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role.

Starting pay for this role will vary based on multiple factors, including location, available budget, and an individual’s knowledge, skills, and experience.  Pay ranges may be modified in the future.

Expedia Group is proud to offer a wide range of benefits to support employees and their families, including medical/dental/vision, paid time