Machine Learning Engineer - Freelance at MacTay Consulting

Job Overview

Location
Lagos, Lagos
Job Type
Full Time
Date Posted
1 year ago

Additional Details

Job ID
90650
Job Views
64

Job Description



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.


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