A first-principles problem solver who challenges the status quo, thinks creatively, and has a strong bias for action.
1012+ years of strong hands-on experience in Advanced Analytics, Data Science, Predictive Modelling, and Deep Learning.
Proven ability to translate business problems into AI/analytics use cases and solution blueprints.
Ability to influence without authority across business and tech teams.
Strong at embedding AI into workflows and driving adoption.
Excellent executive storytelling using data, can explain complex Analysis and AI simply to CxOs.
Solid understanding of statistics, machine learning, and model evaluation techniques.
Strong proficiency in Python, SQL, and ML/DL libraries (PyTorch/TensorFlow, scikit-learn, etc.).
Proven experience with LLMs: prompt engineering, fine-tuning (LoRA/PEFT), RAG, agents, and orchestration frameworks (LangChain, LlamaIndex, or similar).
Experience with NLP, text mining, speech AI (ASR/STT, TTS), and conversational AI pipelines.
Experience with computer vision and video models, embeddings, and familiarity with transformer-based video architectures (e.g., VideoMAE, TimeSformer, etc.).
Experience building multimodal systems combining text, voice, vision, and structured data for decisioning.
Experience in designing system architectures that combine models, APIs, and workflows.
Experience deploying AI systems on cloud platforms (AWS/Azure/GCP); strong exposure to AWS services (Lambda, S3, SNS, SQS, EC2, RDS, KMS, SageMaker). Familiarity with Docker, Kubernetes, CI/CD, and scalable inference pipelines.
Experience in Insurance, BFSI, FinTech, or HealthTech preferred.
Exposure to digital analytics platforms (e.g., Google Analytics, BigQuery) is a plus.
Bachelors or Master’s degree in Engineering, Technology, Statistics, Data Science, or related fields from a reputed institute; MBA is a plus.

Chief Data Scientist

Job Description

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