Understand business objectives, and product requirements and develop ML algorithms that achieve them.
Build Prototypes, and proof of concepts to determine feasibility, then drive data-based decisions.
Run experiments to assess performance and improvements.
Provide ideas and alternatives to drive a product/feature.
Define data and feature validation strategies.
Deploy models to production systems and operate them including monitoring and troubleshooting
Design, build, and manage the data pipelines and infrastructure that collect, store, and process large volumes of transactional and customer data from various sources.
Develop, deploy, and scale machine learning models and applications in production and lower environments
Ensure data quality, security, and availability for the data, notebooks, models, experiments, and applications.
Integrate ML models with the SaaS platform and other services and tools, such as the model registry, feature store, data lake, and event streams.
Collaborate with data scientists to develop and test machine learning models.
Drive code reviews to ensure code quality, maintainability, and adherence to coding standards.
Provide live on-call support by participating in the team on-call rotation and owning production issues from the root cause analysis to a resolution to future prevention.
Partner with cross-functional teams (engineering, product, design, security, compliance, etc.) to bring ideas to life
Build secure, robust, scalable, and performant systems for processing transactions and managing customer data.
Requirements & Skills:
At a minimum, a Bachelor’s in CS or equivalent education and either 3+ years of relevant professional experience or an advanced degree such as a master’s or PhD.
Experience leading projects from architectural design to production, while setting and maintaining high standards of technical excellence across your team.
Effective communication and collaboration skills, and a history of collaborating effectively with your team and cross-functional stakeholders.
Excellent communication and cross-functional collaboration skills to thrive in a fast-paced environment.
Experience with data management, data, and building pipelines.
Experience with building and deploying machine learning models.
Experience with AWS, Snowflake, Databricks, or similar technologies.
