Team Lead Data Scientist (Client Facing)

Role: Team Lead Senior Data Scientist (Engineering / AI)

Industry: Next-generation mortgage intelligence platform (US)

Location: South Africa (Remote)

Employment Type: Full-time Contract

Note: Candidates must be based in South Africa and available to work 08h00-17h00 US Eastern Standard Time (EST).

Note: This client-facing role requires experience with graph databases, particularly Neo4j as well as experience with knowledge graphs, graph-based reasoning, or Graph-RAG architectures.

Introduction:

Our client (US-based) builds advanced AI systems that reason over complex data, documents, and knowledge graphs. Their platform combines machine learning, natural language systems, and graph-based reasoning to automate decision-making in document-intensive domains.

We are looking for a client-facing Team Lead Senior Data Scientist who is comfortable working deep in the stack, from modeling and experimentation to building production systems that integrate models, tools, and data pipelines.

This role is not focused on prompt engineering or simple API wrappers. We are looking for engineers who understand how models work, how to evaluate them rigorously, and how to integrate them into scalable production architectures.

About the Role:

As a technical lead, you will guide and design the development of machine learning and AI systems used in production while working closely with clients, platform engineers, data engineers, and infrastructure teams.

You will translate complex technical concepts into practical solutions and ensure successful delivery of AI systems in real-world environments.

Note: This role is fully remote but candidates must be available to work 08h00-17h00 US Eastern Standard Time (EST).

Responsibilities:

• Lead the design, development, and evaluation of machine learning models, including feature engineering, model selection, and statistical validation
• Guide and mentor data scientists and engineers, setting technical direction and helping the team build scalable AI systems
• Build production-grade Python systems for data processing, model training, and inference pipelines
• Develop NLP systems for document understanding, classification, semantic search, and information extraction
• Design and implement RAG architectures, embedding strategies, indexing approaches, retrieval evaluation, and grounding techniques
• Develop agentic AI systems that coordinate models, tools, and multi-step reasoning workflows
• Engage directly with clients and stakeholders to understand requirements, present solutions, and translate technical capabilities into business outcomes
• Collaborate with platform and infrastructure teams to deploy and operate ML systems in production environments
• Provide technical leadership during client engagements, helping shape AI strategies and guiding implementation decisions
• Contribute to architectural decisions around AI system design and data modeling

Required Skills and Qualifications:

• Strong Python programming for ML and data systems
• Experience designing and training ML models (not solely relying on hosted AI services)
• Deep understanding of ML fundamentals (statistics, optimization, model evaluation)
• Hands-on NLP experience (document extraction, classification, semantic search)
• Experience designing and implementing RAG pipelines and retrieval systems
• Experience building agent-based or tool-using AI systems (planner-executor, multi-agent coordination)
• Experience with production data systems and real-world datasets
• Experience leading technical projects or mentoring engineers / data scientists
• Strong problem-solving ability and translating ambiguous problems into measurable systems

Preferred Qualifications:

• Experience with graph databases, particularly Neo4j
• Experience with knowledge graphs, graph-based reasoning, or Graph-RAG architectures
• Experience deploying ML systems in Azure or AWS
• Familiarity with MLOps practices (containerization, model deployment, monitoring, CI/CD)
• Experience in document-heavy or compliance-oriented domains
• Strong communication and presentation skills with clients or senior stakeholders
• Experience leading technical discussions, workshops, or solution design sessions with customers