Job Description :

A master's or doctoral degree in a relevant field such as computer science, statistics, mathematics, or data science is preferred.

A strong academic background with coursework in machine learning, statistical modeling, data mining, and programming is valuable.

Requirements :

- 7-12 years of practical experience in data science, generative AI, machine learning, and analytics.

- Experience in relevant domains, such as e-commerce, advertising, or retail, may be advantageous.

- Minimum 3-4 years of deep, hands-on expertise in NLP, LLMs, and Generative AI.

- 2+ years of demonstrated experience in leading projects and teams.

- Advanced Proficiency in Python is essential for data manipulation, statistical analysis, and machine learning model development.

Core Skills :

- Strong foundation in machine learning, deep learning, and NLP.

- Hands-on experience with LLMs (GPT, LLaMA, Falcon, Mistral, etc.) and GenAI frameworks (LangChain, Hugging Face, RAG, fine-tuning, LoRA).

- Proficiency in Python, PyTorch/TensorFlow, SQL, and cloud platforms (GCP/AWS/Azure).

- Experience with MLOps frameworks (MLflow, Kubeflow, Vertex AI, SageMaker, etc.

- Strong data engineering skills to build ETL pipelines for large-scale datasets.

- Statistical rigor : hypothesis testing, power analysis, confidence intervals; regression (GLM/GLMM), time-series; causal inference (propensity scores, DiD, RDD) for business impact.

Soft Skills :

- Strong business acumen and ability to map AI/ML solutions to strategic goals.

- Excellent communication and stakeholder management skills.

- Proven track record of mentoring and leading teams, collaborating with cross-functional teams, and communicating effectively with stakeholders