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Senior Machine Learning Engineer with Spotify USA, Inc. 4 World Trade Center, 150 Greenwich Street, New York, NY 10007 *Telecommuting permitted: Work may be performed within normal commuting distance from the Spotify USA, Inc. office in New York, NY.Job Duties: Machine Learning Research: Develop and implement machine learning models to accurately predict and compute user retention probabilities and the lifetime value of over 2 billion users across Spotify’s personalization services. Apply supervised and unsupervised learning methods to create accurate and robust models that can improve business needs, save on costs, and better understand users. Demonstrate understanding on how statistical models can be personalized for predicting personalized user retention. Validate model performance by testing it against many data sets and using various metrics to evaluate model accuracy using offline and online methodologies. Remain up-to-date on the latest trends and innovations in machine learning, data science, and AI, and integrate them into the organization's strategy and product roadmap. Optimize and improve on existing processes and practices in machine learning development, including methods in testing, deployment, scaling, and applications. Analyze large datasets to identify trends and patterns, and develop insights that inform business decisions and improve product offerings. Demonstrate familiarity with data privacy, security, and compliance regulations, such as GDPR and HIPAA, and ability to design machine learning systems that meet these requirements. Machine Learning Backend / Systems: Maintain and develop machine learning systems to serve daily predictions of user retention and user lifetime value, creating various APIs to access the team’s services (e.g. live predictions, insights). Create, test and maintain scalable data pipelines handling petabytes of data. Incorporate statistical methods into offline evaluation tooling to validate new model releases. Evaluate team’s backend systems to save hundreds of thousands dollars in cloud costs per month. Product: Collaborate with cross-functional teams and key stakeholders across the company to design, implement, and validate solutions using new machine learning techniques that improve our understanding of user behavior and drive business growth. Communicate technical concepts and results to non-technical stakeholders, including senior executives, product managers, and business analysts. Finance: Work directly with key stakeholders in finance to define and implement financial metrics used in the calculation of each user’s lifetime value. Maintain a deep understanding of Spotify’s business model, its revenue streams, and profit margins, in order to understand potential impact on machine learning techniques and projections. Other: Mentor and train junior data scientists and machine learning engineers, and contribute to the development of a strong data science community within the company. Speak at internal and external conferences. Experience with data visualization tools and techniques to effectively communicate insights and findings to stakeholders. *Telecommuting permitted: Work may be performed within normal commuting distance from the Spotify USA, Inc. office in New York, NY.Position requirements: Master’s degree (US or foreign equivalent) in Mathematics, Computer Science, Software Engineering, or a related field and four (4) years of experience in machine learning or a closely related field OR Bachelor’s degree (US or foreign equivalent) in Mathematics, Computer Science, Software Engineering, or a related field and six (6) years of experience in machine learning or a closely related field. Must have four (4) years of experience with: conducting machine learning research on statistics and deep learning based algorithms (e.g. Random Forests, K Nearest Neighbors, Reinforcement Learning, and Deep Neural Networks) and translating said research models into production grade machine learning systems handling millions of users and solving crucial business problems; creating personalized statistical models for the task of retention prediction; implementing machine learning systems using Python and popular machine learning frameworks and tools (e.g. TensorFlow, PyTorch, Scikit-learn, Keras, Apache Spark and Ray); working directly with clients and stakeholders to understand their immediate needs in order to customize product and system design to solve their most important problems; developing tools and features to improve how to train and serve Machine Learning models on a big data scale; developing large scale data pipelines on Petabytes scale using advanced SQL queries on cloud computing services including services: Spark, Hive, and Google Bigquery; and data processing, feature engineering, and data normalization techniques to prepare data for improving machine learning models accuracy. Must have two (2) years of experience with: optimizing data and machine learning pipelines to save on compute and storage cloud costs and designing, running, and analyzing A/B experiments on a large scale on new product or feature launches. Salary: $196,460 - $294,690 / yearQualified Applicants: Apply online at https://jobs.lever.co/spotify/e4e99e4e-cf6a-4f90-b602-3da4ef95543e

Minimum Salary: 196,460 Maximum Salary: 294,690 Salary Unit: Yearly