- Migrating to cloud AWS (EC2 and S3). Will work with Data Science team. Need to fill gap b/w Data Scientist and Engineers, transitioning from SAAS to Python.
- Most of the data that team uses is in Snowflake repository.
- Will work on Client Ops/DevOps Practices.
- 3-5 years exp, extensively hands-on individual
- Needs to be an expert to pass on the knowledge to rest of the team on DevOps/MLOps
- Use statistical and machine learning techniques to create scalable analytics solutions within the auto finance space
- Establish scalable, efficient, automated processes for large scale data analysis, model development, model validation and model implementation
- Drive adoption of best practices across the Data Science organizations
- Design and architect modular and reusable code both for use in experiments as well as production environments
- Deliver production-ready code
- Work with the broader Data Science to define the KPIs for machine learning projects
- Provide technical/team guidance and training/mentorship
- Stay abreast of developments in research methodology and changing technologies in the marketplace and proactively identify applications of these latest developments to improve existing methods
- Prepare and present findings to both technical and non-technical audiences
- BA/BS degree or equivalent experience in Computer Science, Information Technology or related disciplines
- Experience with cloud-native architecture and container orchestration (particularly Docker and Kubernetes) preferred.
- 5+ years of production experience working in Data Science, Machine Learning or Software Engineering
- Experience utilizing Github in the Machine Learning pipeline for best practice code management and collaboration
- Solid production experience using Python (including NumPy), PySpark and SQL
- Production experience with Apache Spark
- Strong fundamentals in problem solving, algorithm design and complexity analysis
- Hands-on experience with web APIs, CI/CD for Machine Learning
- Experience implementing Machine Learning pipelines in production environments is a plus
- Experience working with data science within the financial service space is a plus