MacTay Consulting has been in existence for over 28 years in Nigeria. We are a member of TACK and TMI, international consulting companies operating in over 60 countries and with a combined experience of over 80years. Our global network of partners and experience means that our clients enjoy all the benefits of a local office, while drawing upon our multi-cultural knowledge and global delivery resource - whenever required. MacTay’s approach is to work together in partnership with our clients, we aim to be in it for the long term but firmly believe that partnerships are created by ensuring that our clients are able to develop the capability to sustain and drive solutions we co create with them. We always have an 'exit strategy’ - ways to provide our clients with the opportunity to pick up the solution and run with it themselves, while making ourselves available anytime we are invited for advice. It is precisely this approach which has led to some clients choosing to work with us for many years, knowing that we are there to support them in their chosen journey.
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:
Job Requirements
- Candidates should possess relevant qualifications with 3 – 5 years relevant work experience.
Method of Application
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