Key skills
GRPCHadoopMapReducePythonSparkSQLMachine LearningMLMLOpsAnalyticsgRPCLeadershipPrototypingCommunication
About this role
Role Overview
- Work closely with data engineers and data analysts to help build ML
- and statistics-driven data quality and continuous data monitoring workflows
- Solve business problems by scaling advanced Machine Learning algorithms and complex statistical models on large volumes of data
- Own the MLOps lifecycle, from data monitoring to refactoring data science code to building robust model monitoring workflows for model lifecycle management
- Demonstrate strong thought-leadership and consult with product and business stakeholders to build, scale and deploy holistic machine learning solutions after successful prototyping
- Follow industry best practices, stay up to date with and extend the state of the art in machine learning research and practice and drive innovation
- Promote and support company policies, procedures, mission, values, and standards of ethics and integrity.
Requirements
- Bachelor's degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or related field and 3 years' experience in an analytics related field
- Master's degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or related field and 1 years' experience in an analytics related field
- 5 years' experience in an analytics or related field
- Knowledge of the foundations of machine learning and statistics
- Experience with web service standards and related patterns (REST, gRPC)
- Experienced in architecting solutions with Continuous Integration and Continuous Delivery in mind
- Familiar with distributed in-memory computing technologies
- Solid experience working with state-of-the-art supervised and unsupervised machine learning algorithms on real-world problems
- Strong Python coding and package development skills
- Experience with Big Data and analytics in general leveraging technologies like Hadoop, Spark, and MapReduce; Ability to work in a big data ecosystem
- expert in SQL/Hive and ability to work with Spark
- Able to refactor data science code and has collaborated with data scientists in developing ML solutions
- Experience playing the role of full-stack data scientist and taking solutions to production
- Experience developing proper metrics instrumentation in software components, to help facilitate real-time and remote troubleshooting/performance monitoring
- Good effective communication (both written and verbal) skills and the ability to present complex ideas in a clear & concise way, to different audiences.
- A team player with good work ethics.
Tech Stack
- GRPC
- Hadoop
- MapReduce
- Python
- Spark
- SQL
Benefits
- Incentive awards for performance
- Maternity and parental leave
- PTO
- Health benefits