Vacancy expired!
GEICO's Site Reliability Engineering (SRE) team uses machine learning and predictive analytics to improve system reliability to create a superior customer service experience.
We work with the major lines of business at GEICO that deliver mission-critical applications to our agents and our customers. The predictive models ingest machine data from many systems and application sources to build an understanding of the system components that affect customer experience. The SRE team support projects through the entire lifecycle, from problem definition to data exploration, modeling, analysis, and deployment into production. We work in a highly collaborative environment across teams to ensure the model is working as expected and continually tune and address issues as they arise in our changing environment.We are looking for a Systems professional/DevOps Engineer with strong data analytical skills to help develop models that take advantage of Machine Learning/Artificial Intelligence to detect issues before they impact the customer experience. The candidate must have strong analytical skills to gain insights from a myriad of application monitoring and telemetry data in the area of Cloud computing, Microsoft Azure, Dynatrace SaaS, Splunk and SQL Server, and CosmosDB. The candidate must be comfortable working with a wide range of stakeholders and functional teams. The right candidate will have a passion for discovering solutions hidden in data sets and working with stakeholders to improve business outcomes.Key Responsibilities:- Analyzing system infrastructure and performance metrics to identify actionable insights
- Designing and deploying predictive models using Splunk ITSI
- Assessing the effectiveness and accuracy of new data sources and data gathering techniques
- Developing processes and tools to monitor and analyze model performance and data accuracy
- Bachelor's degree in computer science or in a quantitative discipline, such as statistics, data science, mathematics, engineering, physics, etc. Advanced degrees preferred
- 2+ years of combined academic/industry experience with predictive modeling, machine learning, advanced analysis
- Strong programming skills using common data science tools such as Python (strongly preferred).
- Strong skills in data processing using SQL (preferred)
- Solid understanding and experience with advanced statistics and modern machine learning predictive techniques
- Strong skills with Microsoft Azure Cloud Computing Services, Microsoft App Insights, Microsoft Azure Log Analytics, Splunk, Splunk ITSM (preferred)
Vacancy expired!