Machine Learning Engineer

Responsibilities include: 

• Perform a gap analysis to include analyzing the current state, creating a baseline, identifying the gaps between what is known and what is needed, and developing an action plan to mitigate the gaps. 
• Establish a repeatable process to periodically “scrape” and collect skills from a collection of performance reviews.
• Create an access-controlled collection of disparate data sources and database to store collected jobs, competencies, KSAs, and proficiency levels.
• Create a data migration plan to export collected skills and competencies into the Customer’s systems. 
• Scrape, collate, and perform analysis of skill sets from open source, commercially available, and existing databases and applications for addition to the skills repository.
• Scrape, gather, and analyze onboarding data to enrich the skill and competencies repository.
• Review and analyze all Customer service competency data for addition to the skill and competencies repository.
• Collaborate with internal Customer offices to review, analyze, and update competency data from open source, commercially available, existing databases, and applications, in addition to the skill and competencies repository. T
• Evaluate Chatbot and Machine Learning (ML), Artificial Intelligence (AI) offerings, and integration methods, and provide a report on opportunities to integrate with the Customer's systems.
• Evaluate and assess planned system restructuring and its data integration impacts with a new external service provider.
• Support system restructure to understand data standards required and the impact on the Customer’s OPM standardization efforts.
• Create a transition guide or Standard Operating Procedures (SOPs) of activities.
• Create and maintain documentation related to:
• A Skills Taxonomy Gap Analysis Report to include an assessment of the current state, proposed baseline of competencies and KSAs, identification of missing data, and an action plan for gap mitigation.
• System access to database(s), systems used, and databases accessed to perform the work
• Internal and External Key Contacts
• Concerns, risks, and issues regarding data, storage, tools, and access
• Status of deliverables and open actions.

• Active TS/SCI with polygraph.
• Bachelor’s Degree (B.S.) in Computer Science, Software Engineering, Information Management Systems, or a related discipline. Note that years of experience can be substituted in lieu of degree. 
• 9 or more years of demonstrated experience in the following:
• Designing, creating tables, views, relationships, and scripting (SQL) with database systems (e.g., Oracle, MySQL, PostgreSQL, SQL, NOSQL, and/or structured and unstructured data).
• Implementing and using extract, transform, and load (ETL) tools.
• Implementing, using, and creating Data Application Programming Interfaces (APIs) or data services.
• Python, Java, and Scala programming languages.
• Implementing, using, and creating data visualizations.
• Implementing, using, or creating ML/AI software, tools, and services.
• Using or creating Amazon Web Services (AWS)-based analytic tools and services.
• Using and implementing Apache Hadoop.

Desired Qualifications: