Director, Lead Data & Analytics Engineer
About The Position
Morgan Stanley Services Group, Inc. seeks a Director, Lead Data & Analytics Engineer in New York, New York Maintain and support services and capabilities of the firm’s internal search infrastructure. Onboard and index new data sources, clean existing index, improve relevancy algorithms, and apply AIML models to search application. Create data pipelines and ETL processes to facilitate onboarding client data into firm databases. Upgrade software system capabilities to best serve the business needs of end users. Incorporate industry best practices to improve performance and productivity of the firm’s internal search infrastructure. Develop a monitoring mechanism for search infrastructure. Streamline and improve product delivery metrics. Troubleshoot technical issues, perform root cause analysis, and take appropriate action to remediate issues related to discovery, relevancy and data mining.
Requirements
- Requires a Master's degree in Computer Science, Computer Engineering, or a related field plus three (3) years of experience in the position offered or three (3) years of experience as an AI/ML Engineer, Data Scientist, or related occupation.
- Two (2) years of experience with: Java.
- One (1) year of experience with: vended or open-source search engines; Javascript; and Python.
- Any amount of experience with: building and training machine learning models; deploying machine learning models in production; AI chatbot development; Semantic search; Lucidworks Fusion connector configurations; indexing strategies for structured and unstructured data; faceted search; typeahead; relevance boosting; DevOPs; KPI’s; Agile practices; Enterprise Git; GitHub; Jenkins; continuous integration tools, including Artifactory ro, SonarQube, selenium, and Jmeter; load testing; troubleshooting and production support; Docker; Kubernetes; and Azure.
Responsibilities
- Maintain and support services and capabilities of the firm’s internal search infrastructure.
- Onboard and index new data sources, clean existing index, improve relevancy algorithms, and apply AIML models to search application.
- Create data pipelines and ETL processes to facilitate onboarding client data into firm databases.
- Upgrade software system capabilities to best serve the business needs of end users.
- Incorporate industry best practices to improve performance and productivity of the firm’s internal search infrastructure.
- Develop a monitoring mechanism for search infrastructure.
- Streamline and improve product delivery metrics.
- Troubleshoot technical issues, perform root cause analysis, and take appropriate action to remediate issues related to discovery, relevancy and data mining.
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What This Job Offers
Job Type
Full-time
Career Level
Director
Number of Employees
5,001-10,000 employees
