Senior Staff Applied Scientist
About this role
Global Operations Optimization Science and Engineering builds and operates machine learning and optimization systems across supply chain, fulfillment, logistics, delivery, commerce risk detection, and post-purchase experiences. Counterfeit sales on the platform distort market competition and damage customer trust, prompting the creation of an intelligent and comprehensive counterfeit detection system at scale to replace manual and imprecise enforcement methods. A senior staff applied scientist will design and implement end-to-end machine learning systems, formulate complex business problems into machine learning solutions, and drive the technical vision and roadmap for commerce risk detection.
Working closely with product, operations, and back-end engineering teams, the successful candidate will build and optimize scalable machine learning pipelines while mentoring engineering talent. Individuals who thrive in this environment possess deep expertise in classic machine learning algorithms and transformer-based models, and enjoy navigating ambiguity within a fast-paced global organization. The role suits pragmatic technical leaders who combine hands-on production experience with a strong focus on operational excellence and measurable business impact.
What you will do
- Design and implement end-to-end machine learning systems for applications including commerce risk detection, post-purchase experiences, and logistics compliance.
- Formulate real-world business challenges as machine learning problems while driving innovation across e-commerce operations.
- Drive and own the machine learning vision and roadmap for large and complex technical projects.
- Build and optimize machine learning pipelines using tools such as Apache Spark, Airflow, Kubeflow, and MLflow to ensure reproducibility and scalability.
- Define and track key performance metrics to evaluate model impact and identify high-leverage opportunities for improvement.
- Collaborate closely with product, operations, and back-end engineers to align technical solutions with business goals.
- Mentor and grow engineering talent while fostering a culture of technical excellence and continuous learning.
What you need
- Bachelor's degree in computer science, electrical engineering, mathematics, statistics, or a closely related field.
- Minimum of eight years of professional experience in applied machine learning.
- Demonstrated expertise in machine learning, deep learning, and statistical modeling.
- Proficiency in Python and Java, backed by experience in building production-grade machine learning systems.
- Strong communication skills with the ability to explain complex technical concepts to both technical and non-technical stakeholders.
- Proven ability to lead cross-functional teams and deliver results in a multicultural, global organization.
Nice to have
- Master's degree or PhD in relevant technical fields
- Domain knowledge in fraud detection, customer support, and/or logistics
- Hands-on experience with modern ML frameworks such as TensorFlow, PyTorch, Scikit-learn, Keras, XGBoost, LightGBM, and H2o.ai
Benefits
- Annual bonus of 0-20% of base salary
- Medical, Dental, Vision, Life, and AD&D insurance
- 401K Plan with Company Match
- 18-21 days of Paid Time Off (PTO) a year based on tenure and 12 Paid Holidays
- Paid Parental leave and pre-tax commuter benefits
- Free Electric Car Charging Station
Skills and tech stack
Questions candidates ask
What is the compensation range for this position?
The base pay for this position ranges from $159,000 to $324,000 per year. Pay is based on several factors including market location and may vary depending on job-related knowledge, skills, and experience.
What does the hiring process look like?
The recruitment process consists of an application review, a phone interview, and an onsite or virtual onsite interview before an offer is made. The exact nature of the process may vary according to the specific job and scheduling circumstances.
What additional compensation is offered beyond base salary?
Other compensation includes bonuses, equity, or other forms of compensation offered to the hired applicant in addition to their established salary. The annual bonus is targeted at 0-20% of the base salary.