Engineering Manager - Data Science

Role Overview

We are seeking a seasoned and visionary Data Science Manager with deep expertise in AI/ML, including

Classical ML, Deep Learning, NLP, and Generative AI. The ideal candidate will have a strong technical

foundation, proven leadership experience, and a passion for solving complex business problems using datadriven approaches. This role requires a balance of strategic thinking, hands-on technical execution, and team leadership.

Required Skills & Qualifications :

Key Responsibilities :

Leadership & Strategy :

- 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 AIdriven innovation.

- Advocate for ethical AI practices and model governance.

Technical Execution :

- 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.

Project & Stakeholder Management :

- 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.

- 15+ years of experience in Data Science, Machine Learning, and AI.

- Strong academic background in Computer Science, Statistics, Mathematics, or related field (PhD or

- Hands-on experience with :

o Classical ML : XGBoost, Random Forest, SVM, etc.

o Deep Learning : CNNs, RNNs, LSTMs, Transformers

o NLP : BERT, GPT, LLaMA, T5, etc.

o 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 Azure, Azure Copilot Studio, Azure Cognitive Services

- Experience with Azure AI Foundry would be a strong added advantage

- Publications or patents in AI/ML domains.

- Good to know other cloud platforms like AWS, GCP and their respective data and AI services.

- Excellent communication and storytelling skills.

- Strong problem-solving and analytical thinking.

- Ability to inspire and lead high-performing teams.

- Adaptability in a fast-paced, evolving tech landscape.

- 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