Lead Data Scientist

Description

We are hiring! Integrant is looking for game changers to join our team as Data Scientist - AI & Machine Learning with the below roles and responsibilities:

• Use mathematics, statistics, machine learning, and artificial intelligence techniques to extract knowledge and insights from structured, semi-structured, and unstructured data.
• Design, develop, evaluate, and deploy predictive and prescriptive machine learning models.
• Conduct open research and experimentation to develop innovative solutions for complex client challenges.
• Engage with clients and stakeholders to understand business needs and translate them into AI and data science solutions.
• Design and implement end-to-end machine learning and generative AI solutions.
• Build and optimize retrieval-augmented generation (RAG) systems and intelligent agent-based applications.
• Develop scalable model deployment and monitoring solutions using MLOps best practices.
• Monitor model performance, detect concept drift, and continuously improve deployed systems.
• Collaborate with software engineering teams to productionize AI applications and ensure reliability, scalability, and maintainability.
• Mentor and coach junior data scientists and machine learning engineers.
• Lead technical discussions, knowledge transfer sessions, and client-facing AI engagements.
• Stay current with emerging AI, machine learning, MLOps, and generative AI technologies and frameworks.

Requirements

Education & Experience

• 10+ years of professional experience, including 7+ years in data science, machine learning & MLOps.
• MSc in computer science, data science, artificial intelligence, statistics, mathematics, engineering, or a related quantitative discipline.
• PhD is preferred in a related field.
• Experience mentoring, coaching, or leading technical team members.

Data Science & Machine Learning

• Strong foundation in machine learning techniques including classification, regression, clustering, association rule mining, feature engineering, and model evaluation.
• Experience with deep learning concepts and frameworks.
• Extensive hands-on experience with Python and the data science ecosystem.
• Experience with one or more ML frameworks such as Scikit-Learn, TensorFlow, Keras, or PyTorch.
• Experience conducting research, experimentation, and hypothesis-driven analysis.

MLOps & Production AI

• Experience deploying and managing machine learning models in production environments.
• Experience monitoring model performance, detecting concept drift, and driving continuous improvements.
• Hands-on experience with MLOps practices, CI/CD pipelines, model versioning, experiment tracking, monitoring, and observability.
• Experience deploying AI/ML solutions on cloud platforms such as Azure, AWS, GCP, or Databricks.
• Experience with ML platforms and services including Azure ML, AWS SageMaker, or Google Vertex AI.
• Familiarity with deployment and serving tools such as MLflow, FastAPI, and Streamlit.

Generative AI & Agentic AI

• Hands-on experience building retrieval-augmented generation (RAG) solutions and semantic search applications.
• Experience working with vector databases such as Pinecone, Weaviate, Chroma, Milvus, or Azure AI Search.
• Experience using LLM orchestration frameworks such as LangChain, LangGraph, or similar technologies.
• Experience working with agentic AI frameworks such as LlamaIndex, CrewAI, AutoGen, or equivalent.
• Experience implementing MCP (Model Context Protocol), tool calling, and function-calling workflows.
• Strong understanding of prompt engineering techniques and LLM optimization.
• Experience evaluating LLM applications using frameworks such as LangSmith, RAGAS, or similar tools.
• Experience with embeddings, vector retrieval, semantic search, fine-tuning, and LoRA techniques.

Nice to Have

• Advanced AI & data science
• Reinforcement learning (RL)
• Optimization techniques, including single-objective and multi-objective optimization
• Stochastic local search methods
• Knowledge graphs and graph machine learning

Cloud & Data Engineering

• Experience building large-scale data pipelines on Azure, AWS, or GCP.
• Experience with Databricks and Apache Spark.
• Experience with distributed data processing architectures.

Leadership & Consulting

• Experience leading AI initiatives and technical strategy.
• Experience working directly with international clients and stakeholders.
• Experience defining AI architecture, standards, and best practices across teams.

Benefits

• Salary paid in USD
• Six-month career advancing opportunities
• Employee parking space
• Supportive and friendly work environment
• Premium medical insurance (employee and family)
• English language development courses
• Interest-free loans paid over 2.5 years
• Technical development courses
• Planned overtime program (POP)
• Employment referral program
• Premium location in Maadi and Nasr City
• Social insurance
• Opportunity to travel and work onsite with U.S. customers
• In-house technical and English training programs
• Dedicated learning time (check out our 4Plus1 Program)
• Flexible work schedules
• Perks: events, sponsored lunch, game area, rooftop hangout, and more!