Machine Learning Engineer - Freelance at MacTay Consulting

Job Summary

• In line with the Digital Services division's strategic objectives for personalized digital interactions and optimized mobile marketing, we are seeking a skilled Machine Learning Engineer for a temporary role.
• This individual will contribute to Customer Value Management (CVM) by employing advanced machine learning techniques to analyze customer behavior and preferences, translating company's data insights into actionable models.
• The engineer will play a pivotal role in refining digital channels and mobile marketing campaigns, developing algorithms for enhanced user engagement, predicting customer preferences, and fostering personalized interactions.
• This freelance position involves collaborative work to seamlessly integrate machine learning solutions, ensuring a cohesive user experience and amplifying the effectiveness of our digital assets within the context of our brand identity.
• This opportunity allows the engineer to apply their expertise to dynamically influence the evolution of our digital ecosystem and mobile marketing initiatives.

Project Objective

• Data Analysis and Insights:Identify actionable insights from customer data for CVM and mobile marketing.
• Machine Learning Models:Develop models predicting and responding to customer preferences.
• Digital Platform Integration:Integrate machine learning solutions into digital platforms for CVM.
• Personalization Strategies: Execute personalized customer interactions based on ML insights.
• Optimization of Campaign Assets: Refine mobile marketing campaigns using advanced machine learning.
• User Experience Enhancement: Implement ML solutions for a seamless user experience in line with CVM.

Job Responsibilities

• The following approach will be followed during the execution of the project. The resource is expected to align and provide all necessary deliverables as highlighted below:

Collaborative Project Kickoff:

• Initiate a collaborative kickoff meeting involving stakeholders to define project objectives, expectations, and timelines.
• Establish clear communication channels to ensure alignment among all parties.

Data Collaboration and Assessment:

• Collaborate closely with data management teams to gain a comprehensive understanding of available data on company's server.
• Assess data quality, relevance, and completeness to inform subsequent model development steps.

Objective Refinement with Stakeholders:

• Engage stakeholders in refining and finalizing specific objectives for CVM and mobile marketing improvement using machine learning.
• Ensure that objectives align with the overall goals of the organization.

Transparent Model Design and Planning:

• Collaborate with stakeholders to transparently define the scope and requirements of machine learning models.
• Develop a clear plan for model architecture, incorporating feedback from stakeholders.

Iterative Data Preprocessing and Feature Engineering:

• Implement an iterative process for data preprocessing, addressing missing values, outliers, and ensuring compatibility with machine learning algorithms.
• Collaborate with stakeholders to identify relevant features and iteratively engineer new ones to enhance model performance.

Continuous Stakeholder Engagement:

• Maintain continuous collaboration with stakeholders throughout the model development process.
• Gather feedback at key stages to ensure that the evolving models align with stakeholder expectations.

Incremental Model Training and Evaluation:

• Adopt an incremental approach to model training, allowing for frequent evaluation and refinement.
• Assess model performance using relevant metrics, iterating on design and parameters to achieve optimal results.

Comprehensive Documentation and Knowledge Transfer:

• Create comprehensive documentation outlining the model development process, parameters, and methodologies.
• Conduct knowledge transfer sessions to ensure that stakeholders understand the models, their interpretations, and potential applications.

Strategic Deployment and Ongoing Monitoring:

• Strategically deploy finalized machine learning models to production environments.
• Implement robust monitoring systems to track model performance in real-world scenarios, addressing any issues promptly.

Work Hours:

• Flexible, but not strictly between 8 am and 5 pm.
• Must be able to work remotely.
• Must have work tools including laptops, and stable power/access to high-speed internet.

Relationship - Interpersonal relationship:

• Must maintain good working relationship across all levels of staff.

Quality of Work:

• Must maintain professional standards expected of a consultant.
• Ability to multitask.
• Delivery to specific timelines, output and consistency.

Adherence to company's Staff Code of Conduct:

• Office Etiquette.

Job Requirements

• Candidates should possess relevant qualifications with 3 – 5 years relevant work experience.