CA Global Headhunters is an international recruitment and staffing company with an in-depth focus on Recruitment in Africa. We recruit talent of the highest standard across African Sectors in Mining, Oil & Gas, Engineering, Banking, Finance, Legal, Insurance, Commodities and Agriculture. As the African markets further grow and develop, our skills and expertise simultaneously grow too, ensuring that we deliver the best service for both clients and candidates. Our extensive candidate network built up over 8 years comprises the most diverse, skilled and experienced candidates. We have access to resources, networks, and relationships globally which enable us to understand our clients’ cultures, operations, business strategies and industries. With offices in South Africa, Mozambique, China and Geneva we are always on par with new technologies and trends which assist us in sourcing the best talent. Whatever stage of the project life cycle, we can effectively put forward the right candidates with the right skills.
Job Description
- Our client a leading bank in Nigeria is seeking a qualified professional to join their team as the Domain Leader, Data Science/Enterprise Analytics.
- This is a unique opportunity for an experienced ML scientist and hands-on NLP/Gen AI/ LLM senior scientist to grow into the next step in their career journey and apply her or his domain expertise in NLP, deep learning, GenAI, and LLMs to drive business value for multiple stakeholders while mentoring and growing a Data Science and analytics unit.
- The ideal candidate must have deep design and hands-on development expertise in ML, LLMs, model development and integrating ML solutions with business functions to create the next generation of AI-powered capabilities.
- Reporting to the Chief Data Officer within the Enterprise Data Management & Transformational Analytics function of the Bank, this role is critical to the Bank’s data agenda.
Responsibilities
- Analytics, ML, Gen AI, NLP, LLM Strategy: Develop and implement ML modeling and LLM development and fine-tuning strategies, best practices, and standards to enhance AI ML model deployment and monitoring efficiency. Develop roadmap and strategy for NLP, LLM, Gen AI model development and lifecycle implementation.
- Analytics, ML, Gen AI, NLP, LLM Model Design and Development: Responsible for the design and development of custom ML, Gen AI, NLP, LLM Models for batch and stream processing-based AI ML pipelines including data ingestion, preprocessing modules, search and retrieval, Retrieval Augmented Generation (RAG), NLP/LLM model development and ensure the end-to-end solution meets all technical and business requirements, and SLA specifications. Work closely with members of technology and business leads and their teams in the design, development, and implementation of the ML model solutions.
- ML, NLP, LLM Model Evaluation: Work closely with the MLOps team to create and maintain robust evaluation solutions and tools to evaluate model performance, accuracy, consistency, reliability, during development, UAT. Identify and implement model optimizations to improve system efficiency.
- NLP, LLM, Gen AI Model Deployment: Work closely with the MLOps team for the deployment of machine learning models into production environments, ensuring reliability and scalability.
- Business Intelligence Propagation: Drive the widespread growth of Business intelligence capabilities across the Bank’s functions.
- Internal Collaboration: Collaborate closely with product teams, business stakeholders, MLOps, machine learning engineers, and software engineers to ensure smooth integration of machine learning models into production systems.
- Stakeholder Engagement and Collaboration: Collaborate closely with business and PM stakeholders in roadmap planning and implementation efforts and ensure technical milestones align with business requirements.
- Mentorship: Recruit, develop and mentor technical AI/ML, NLP, LLM, Gen AI talent on the team Provide guidance and mentorship to junior ML scientists, fostering their professional growth and development.
- Documentation: Maintain comprehensive documentation of ML modeling processes and procedures for reference and knowledge sharing.
- Standards and Best Practices: Ensure the use of standards, governance and best practices in ML model development, and adherence to model and data governance standards.
- Problem Solving: Troubleshoot complex issues related to machine learning model development and data pipelines and develop innovative solutions.
- Collaborate with global and regional cross-functional teams including engineering, operations, tech services, supply chain, to define data platform requirements, and develop machine learning models and analytics solutions that deliver business outcomes.
Requirements
- Bachelor's or Master's degree in Computer Science, Mathematics or Statistics , Computational linguistics, Engineering, or a related field.
- 10+ years of professional hands-on experience leveraging large sets of structured and unstructured data to develop data-driven tactical and strategic analytics and insights using ML, NLP, computer vision solutions.
- Demonstrated 4+ years hands-on experience with Python, Hugging Face, TensorFlow, Keras, PyTorch, Spark or similar statistical tools. Expert in python programming.
- 4 or more years project leadership experience including Agile project management, Scaled Agile Frameworks (SAFE)
- 5+ years hands-on experience developing natural language processing (NLP) models, ideally with transformer architectures.
- 5+ years’ experience with implementing information search and retrieval at scale, using a range of solutions ranging from keyword search to semantic search using embeddings.
- Strong knowledge of and measurable hands-on experience with developing or tuning Large Language Models (LLM) and Generative AI (GAI)
- Experience in creating reports, projections, models, and presentations to support business goals and outcomes.
- Ability to exercise independent judgment and decision making on complex issues regarding initiatives, technical and business goals and related tasks.
- Experience with mentoring junior ML scientists,
- Ability to works under minimal supervision, using independent judgment.
- Excellent written & verbal communication and stakeholder management skill
- Strategic thinker and influencer with demonstrated technical and business acumen and problem-solving skills.
- Experienced with NLP, LLMs (extractive and generative), fine-tuning and LLM model development. Strong familiarity with higher level trends in LLMs and open-source platforms
- Nice to have: Experience with contributing to Github and open source initiatives or in research projects
Benefits And Contractual Information
- Full time position in office
Method of Application
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