Data Quality Implementation Lead

Remote, US Only

No. of opening

3

Job Description

  • Identify root cause, resolve, test, and document fixes for defects and minor enhancements by following through appropriate change management processes.

  • Ensure that Machine Learning (ML) applications/algorithms Pipelines are working in production environment Proactively capture and ensure alignment to daily operational performance metrics, ensuring end-to-end visibility on the health of the Machine Learning (ML) applications/algorithms.

  • Deploying, monitoring and troubleshooting of Machine Learning (ML) applications/algorithms.

  • Ensure that internal production support tools and documentation are accurate and continually up to date. 

  • Proactively work with internal delivery teams to get to the root cause of data processing or other systems issues.

  • Ensure that deviations from standard processes and routines are identified, captured and work through to resolution as defined by standard tools and processes.

  •  Ensure that Channel (Consumers) Integration capabilities and partnerships are well understood, documented Help govern and support Customer framework and utilization.

  •  Proactive in recognizing potential operation issues and risks, actively bringing timely insights and suggestions to bear in mitigation strategies. 

  • Analyzes and interprets collected operations data, developing reports and analytics techniques to spot underlying trends and opportunities for improvement.

  • Work directly with internal and external teams to understand the holistic end-to-end role of Machine Learning algorithms and models. 

  • Ensure the security and integrity of solutions including compliance with Navy Federal, industry engineering and Information Security principles and practices. 

  • Recognize potential issues and risks during the analytics project implementation and recommend mitigation strategies.

  •  Document best practices for data analysis, data engineering, and evangelize their usages. 

  • Develops reports and presentations for senior management, as needed. 

  • Key point of contact between the data analyst/data engineers and the Production support teams 

  • Perform other duties as assigned

Requirements

  • Bachelor’s degree in Information Systems, Computer Science, Engineering, or related field.

  • Proficient in building and operationally supporting cloud enabled enterprise solutions leveraging Azure IaaS/PaaS; Azure Data Lake, Azure Machine learning, ML Studio, Data Factory, Apache Spark / Azure Databricks capabilities in financial services, or similar, sector.

  • Familiarity with Machine learning workflow, Text analytics, Regression, and Classification algorithms.

  • Experience with a Machine Learning (ML) technology stack such as R, Python, Azure ML, Azure HD Insights

  • Hands-on experience supporting Model training, evaluation, validation, serving and monitoring.

  • Proficient using enterprise logging and monitoring tools such as Azure Log Analytics and Splunk to develop complex queries to provide data driven operations support for Analytics & BI solutions.

  • Proficient with tools such as Service Now to track and manage production Incidents.

  • Able to understand data models, large datasets, business/technical requirements, BI tools, data warehousing, statistical programming languages and libraries.

  • Experience in working with enterprise change management tools by following ITIL best practices.

  • Experience in designing data lake storage structures, data acquisition, transformation, and distribution processing.

  • Advanced experience in SQL programming

  • Experience with agile delivery using Jira, or Azure DevOps.

  • Ability to understand and support highly complex data processes and analytical models which support strategic business outcomes.

  • Excellent written and oral communication skills.

Qualifications 

  • Minimum three to five years of experience in supporting complex operations in large organizations

  • ITIL Certification in service operations

  • Ability to interpret complex mainframe copybooks, and relational database concepts

  • Prior experience in the Financial Industry

  • Follow instructions, standards, and procedures