Associate Lead Data Science

Key Responsibilities

• Lead the development and deployment of advanced data science and AI solutions across Machine Learning (ML) Deep Learning (DL) Generative AI and Agentic AI use cases
• Lead the end-to-end model lifecycle management including data ingestion feature engineering model development evaluation deployment monitoring and retraining
• Lead the development and operationalization of Generative AI and Agentic AI systems including prompt engineering orchestration frameworks tool integration and autonomous agent workflows
• Collaborate with cross-functional teams (Engineering Data Engineering Product QA DevOps) to deliver robust AI-powered solutions
• Provide technical leadership and mentorship to data scientists and ML engineers driving capability development and code quality standards
• Ensure AI solutions comply with organizational governance frameworks including security privacy ethical AI and regulatory requirements
• Evaluate and integrate modern AI/ML tools frameworks and platforms (e.g. model serving frameworks vector databases orchestration tools)
• Translate complex business problems into scalable AI solutions and communicate outcomes effectively to stakeholders and leadership

Person Specifications

• Bachelors degree in IT Computer Science Software Engineering Data Science Engineering Mathematics or a related field
• 4-5 years of professional experience in Data Science AI or ML working in production-grade environments

Technical Expertise

• Strong hands-on experience in Machine Learning and Deep Learning (supervised/unsupervised learning NLP computer vision)
• Practical experience in Generative AI (LLMs prompt engineering RAG pipelines embeddings fine-tuning)
• Experience designing and implementing Agentic AI systems (multiagent orchestration tool usage autonomous workflows)
• Solid knowledge of MLOps practices (model lifecycle management CI/CD monitoring retraining pipelines)
• Experience in LLMOps (prompt/version management evaluation frameworks guardrails cost optimization observability)
• Proficiency in Python and common AI/ML frameworks (e.g. TensorFlow PyTorch Scikit-learn)
• Experience with cloud platforms (AWS Azure or GCP) and cloudnative platforms & services (e.g. Copilot Studio Bedrock Vertex AI Azure OpenAI)
• Familiarity with data engineering concepts (ETL pipelines feature stores data lakes/warehouses)

Leadership & Soft Skills

• Strong architectural thinking and problem-solving skills with the ability to design scalable AI systems
• Proven ability to lead teams mentor engineers and drive delivery in fast-paced environments
• Excellent communication skills with the ability to engage both technical and non-technical stakeholders
• Experience working within governance frameworks (e.g. AI governance security compliance)
• Strong ownership mindset with a focus on quality performance and business impact

Vendor submissions - 12 months