Job Description & How to Apply Below
A hands-on Applied AI leader to both build AI systems and drive enterprise adoption . To work closely with the Leadership Team, and functional leaders to design, deliver, and embed AI into core workflows across insurance value chain including sales, underwriting, and operations.
To identify high-impact opportunities, translate business problems into AI solutions, and ensure successful deployment and adoption of AI systems.
Key Focus Areas:
Own end-to-end delivery of AI systems, from problem framing to production and adoption.
Translate business problems into analytical / AI problem statements and architect complete solutions.
Hands-on design and development of ML/GenAI driven workflows
Own AI products end-to-end, driving change management and adoption to embed AI into workflows across the value chain
Track impact and continuously improve models and processes.
Lead by example in execution while mentoring engineers and data scientists.
Qualifications &
Competencies:
A first-principles problem solver who challenges the status quo, thinks creatively, and has a strong bias for action.
10–12+ 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/Tensor Flow, scikit-learn, etc.).
Proven experience with LLMs : prompt engineering, fine-tuning (LoRA/PEFT), RAG, agents, and orchestration frameworks (Lang Chain, Llama Index, 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, Time Sformer, 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, Sage Maker). Familiarity with Docker, Kubernetes , CI/CD, and scalable inference pipelines.
Experience in Insurance, BFSI, Fin Tech, or Health Tech preferred.
Exposure to digital analytics platforms (e.g., Google Analytics, Big Query) is a plus.
Bachelor’s or Master’s degree in Engineering, Technology, Statistics, Data Science, or related fields from a reputed institute; MBA is a plus.
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