Machine Learning Engineer at Maryland Global Initiatives Corporation Nigeria (MGIC)

Job Description

• The Health Informatics Machine Learning Engineer will collaborate with the program team on developing and evaluating machine learning models using large datasets such as treatment data.
• You will own scaling up successful prototypes and implementing a reliable automated production workflow for the model.
• You will collaborate with software development engineers to integrate the model to gain insights.

Duties and Responsibilities
Leadership:

• Technical Expertise:
  • Design / implement a system orchestrating machine learning workflows
  • Build tools to enable our engineers to be efficient in developing new AI solutions
  • Explore ideas for practical and reliable models for data label quality and various label supervision sources
  • Maintain and support software solutions post-production
  • Implements and debugs some of the more involved/complex functionality.
  • Use quantitative analysis and the presentation of data to see beyond the numbers and understand what drives our numbers and provide insights.
  • Research, design and implement descriptive, predictive, and inferential models using data science and machine learning techniques to build solutions for core business cases.
• Representation:
  • Collaborate with the government and other stakeholders on e- initiatives by attending TWG meetings, and implementation all activities designed by the government
  • Attend designated meetings in relation to cross-cutting issues at different levels e.g. within the organization (Team lead meetings, general staff meetings), outside (GON, various Partners meetings).
• Communication:
  • Maintain reports and documentation that are consistent with the task at hand and available to all concerned parties via emails or standard archiving options
  • Connects easily with supervisees and colleagues at all levels in a professional manner.
• Creativity:
  • Generate solutions or approaches to the most demanding problems within the team
  • Establish workable, prioritized, and highly effective problem-solving plans for each problem.

Team Coordination and Supervision

• Provide appropriate mentoring and support to each supervisee addressing their individual assigned task - (one on one physical visits, monthly meetings, and documentation communication to each/all supervisees)
• Give supervisees the information, technology, and reference materials necessary to perform their jobs
• Assign tasks to supervisees to build their capacity and demonstrate their skills in the task in:
• Site support: Each supervisee should have a copy of what sites have been assigned to them with a detailed SOW
• Developments: specific roles of each staff who will be documented and communicated to the staff for each development activity
• Desk activities: Each supervisee should be made aware of the sites that they are responsible for reporting. Feedback on reporting rates and quality of data entered should be shared and discussed with supervisee routinely
• Conduct an annual performance development plan and appraisal for each supervisee.
• Recommend performance awards and/or merit increases when appropriate. As merit increases and award programs are implemented, supervisors will be required to provide evaluations that demonstrate the performance of eligible supervisees
• Sign monthly timesheets and approve requests for time off. Your signature on a time record means you concur with the hours worked as recorded by your supervisee, including time taken off that may result in the supervisees inability to complete the required task
• Identify and support supervisees to complete at least 1 capacity building activity within the year relevant to the project
• Help supervisees address and resolve a wide variety of concerns and complaints. These typically involve job duties and job descriptions, performance standards, and relations with coworkers.

Qualifications
Education:

• Bachelor's degree in Computer Science, Electrical Engineering, Computer Engineering or similar technical discipline; or, equivalent demonstrable experience.

Language:

• Fluency in English (speaking, reading, and writing).

Experience:

• Three (3) plus years of systems development experience
• Proven work experience as an ML engineer.

Specialized Experience:

• Experience building and interpreting machine learning models on real business data.
• Advance knowledge and experience of SQL and ability to visualize data in an easily understandable way to stakeholders or non-technical people.
• Strong Python, and SQL experience, including manipulating large datasets
• Experience taking ML models to production
• Experience and knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
• Experience in design, implement and operate data pipelines and data integration layers to producing Machine Learning modeling
• Experience building and using analytics tools to provide actionable insights and key business performance metrics
• Experience working with distributed and high-scale systems
• Experience with stream and batch data processing.

Skills and Abilities:

• Strong backend coding skills desirable (e.g. Python, Java, Scala)
• Ability to collaborate with Data Engineers and the Product Team
• Ability to work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
• Strong organizational, time management, computer and communication skills, leadership, coaching, and team-building skills to strengthen and cultivate relationships to help achieve organizational goals.
• Ability to recognize the sensitivity to individual organizations' needs and the impact on services of the introduction of IT solutions.
• Ability to perform in a team environment.
• Curious and eager to learn and improve.
• Keen to get involved in a hands-on way, suggesting new feature ideas and always on the lookout for the next growth / optimization opportunity.

General Abilities:

• Ability to multi-task
• Analytical skills
• Ability to follow verbal or written instructions
• Thinking analytically, Communication
• Using effective verbal communication
• Using effective written communication
• Handling stress & emotions
• Concentrating on tasks
• Making decisions
• Adjusting to change
• Examining/observing details
• Sitting for long periods at a time.