Drive data and ML-driven solutions for diverse engineering use cases such as demand forecasting, capacity planning, and management, or fraud and abuse prevention
Architect and build end-to-end ML models to drive data-driven decisions
Be an ML thought partner to our stakeholders
Conduct data exploration, and analysis and provide ML consultancy
Drive and maintain a culture of quality, innovation, and experimentation
Work in an Agile environment that focuses on collaboration and teamwork
Requirements & Skills:
Bachelor’s degree in Computer Science, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study, and/or equivalent work experience
5+ years of equivalent data science experience, with 2+ years of relevant ML experience
Expertise in at least one of data science, machine (or deep) learning algorithms, and statistical methods to solve real-world engineering problems
Comfortable operating at all levels of the predictive stack and user behavior modeling including data collection, feature engineering, batch training and low-latency online serving
Strong mathematical skills with knowledge of statistical methods
MS or PhD in Computer Science or related fields
Familiarity with Python development ecosystem and technologies like Databricks, S3, Spark
Experience with graph-based data workflows such as Apache Airflow, Meson
Mentor colleagues on best practices and technical concepts of building large-scale solutions
