Hybrid Data Science Manager

at Egon Zehnder

• Job title: Data Science Manager
• Job type: Full Time
• Experience level: Senior, Lead
• Salary: Not specified
• Degree requirement: Postgraduate Degree
• Tech skills: Airflow, AWS, Azure, Cloud, Google Cloud Platform, Python, Scikit-Learn, SQL
• Location requirements: Hybrid, Gurugram, India

About the role

• Data Science Manager at Egon Zehnder overseeing AI/ML projects and team mentorship. Driving innovation through data-driven solutions in a collaborative environment.

Responsibilities

• Lead and mentor a team of data scientists, ML engineers, and research scientists.
• Define and drive the AI/ML roadmap aligned with business goals.
• Collaborate with cross-functional teams (Product, Engineering, Business) to identify opportunities for AI-driven innovation.
• Advocate for ethical AI practices and model governance.
• Architect and implement scalable ML solutions using classical algorithms and deep learning frameworks.
• Design and deploy NLP models for various tasks.
• Build and fine-tune Generative AI models for diverse use cases.
• Conduct rigorous experimentation, model validation, and performance tuning.
• Manage multiple AI/ML projects from ideation to production.
• Translate business requirements into technical specifications and actionable insights.
• Present findings and recommendations to senior leadership and stakeholders.

Requirements

• 15+ years of experience in Data Science, Machine Learning, and AI.
• Strong academic background in Computer Science, Statistics, Mathematics, or related field (PhD or Master’s preferred).
• Hands-on experience with:
• - Classical ML: XGBoost, Random Forest, SVM, etc.
• - Deep Learning: CNNs, RNNs, LSTMs, Transformers
• - NLP: BERT, GPT, LLaMA, T5, etc.
• - GenAI: Diffusion models, LLM fine-tuning, prompt engineering
• Proficiency in Python, SQL, and ML libraries (scikit-learn, Hugging Face, LangChain, etc.).
• Experience with cloud platforms (Azure, AWS, GCP) and MLOps tools (AML, MLflow, Kubeflow, Airflow).
• Strong understanding of data architecture, feature engineering, and model deployment pipelines.
• Experience with vector databases, retrieval-augmented generation (RAG), and semantic search.
• Familiarity with LLMOps and GenAI safety frameworks.
• Experience with Aure, Azure Copilot Studio, Azure Cognitive Services
• Publications or patents in AI/ML domains.
• Good to know other cloud platforms like AWS, GCP and their respective data and AI services.

Benefits

• 5 Days working in a Fast-paced work environment
• Work directly with the senior management team
• Reward and Recognition
• Employee friendly policies
• Personal development and training
• Health Benefits, Accident Insurance