IND Lead Engineer Data

The Hartford India; Hyderabad; In loco; INR 4.000.000 - 7.000.000; Tempo pieno

Descrizione del lavoro

The Hartford India in Hyderabad is seeking a Lead Engineer, Data (GCC063) to drive advanced analytics initiatives across insurance domains. You will architect and implement ML, NLP, and GenAI solutions, design data models, and partner with business teams to translate insights into strategy.

You’ll work with Python, SQL, cloud platforms like Vertex AI or SageMaker, and modern data architectures, delivering reliable analytics pipelines and governance aligned with regulatory requirements.

Competenze

• Experience in statistical modeling, machine learning, and advanced analytics using Python (pandas, NumPy, scikit-learn) and strong SQL.
• Experience across the end-to-end modeling and analytics lifecycle, including requirements gathering, experiment design, offline evaluation, and basic production monitoring.
• Solid understanding of core ML, deep learning, and NLP algorithms and architectures.
• Experience designing BI and semantic layer solutions, with dimensional modeling and data warehouse/data lake environments.
• Experience evaluating models with metrics and monitoring, including A/B testing and drift detection.
• Experience designing, developing, and deploying conversational AI solutions, including RAG pipelines.
• Experience with cloud AI platforms (Vertex AI, SageMaker, Bedrock, Azure AI).
• Experience with Git, Unix, reproducible notebooks/pipelines, and container concepts.
• Ability to translate complex technical designs into business outcomes and strategy.
• Foundational knowledge of insurance products, underwriting, claims, pricing, and regulatory contexts.
• Experience with GenAI, embeddings, retrieval strategies, prompt engineering, and knowledge graphs.

Conoscenze

Python

SQL

Machine Learning

NLP

Deep Learning

PyTorch

TensorFlow

Git

Unix

Data Modeling

Strumenti

Vertex AI

SageMaker

Bedrock

Data Warehouses

Data Lakes

Descrizione del lavoro

IND - Lead Engineer, Data - GCC063

We’re determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals – and to help others accomplish theirs, too. Join our team as we help shape the future.

Job Description

• Experience in statistical modeling, machine learning, and advanced analytics using Python, including pandas, NumPy, scikit-learn, and strong SQL for complex data exploration, feature engineering, and knowledge preparation; familiarity with PyTorch and/or TensorFlow preferred.
• Experience across the end-to-end modeling and analytics lifecycle, including requirements gathering, experiment design, offline evaluation, and basic production monitoring and validation of AI and BI solutions.
• Solid understanding and practical application of core machine learning, deep learning, and natural language processing algorithms and architectures.
• Experience designing and implementing business intelligence and semantic layer solutions, including dimensional modeling, fact tables, metrics definition, and operating within data warehouse or data lake environments.
• Experience designing and operationalizing evaluation and monitoring strategies, including test set creation (gold and/or synthetic), defining and tracking metrics such as classification, forecasting, ranking/IR, RAG faithfulness and truthfulness, and customer or operational KPIs, with support for A/B testing and drift detection.
• Experience designing, developing, and deploying conversational AI solutions, including chatbots, virtual assistants, intelligent agents, and Retrieval-Augmented Generation (RAG) pipelines.
• Experience working with unstructured data, including document parsing and OCR fundamentals, robust text normalization, metadata and lineage awareness, and PII detection or redaction considerations for insurance documents.
• Experience working with cloud-based AI and analytics platforms such as Google Vertex AI, AWS SageMaker or Bedrock, or Azure AI Services, supporting experimentation, deployment, and conversational AI use cases.
• Experience using Git and Unix-based environments, building reproducible notebooks or pipelines, and applying basic container and cloud concepts to support reliable analytics and AI workflows.
• Experience communicating complex technical designs, trade-offs, evaluation results, and risks to both highly technical and non-technical business audiences, translating insights into clear business outcomes and strategy.
• Foundational knowledge of insurance products, processes (including underwriting, claims, and pricing), and regulatory environments, with demonstrated ability to apply analytics and AI solutions within a regulated industry context.
• Experience with advanced NLP and Generative AI capabilities, including embeddings, hybrid and dense retrieval strategies, advanced chunking, prompt engineering, structured outputs, and integrating knowledge graphs into RAG solutions for improved grounding.
• Experience or exposure to advanced GenAI applications in insurance, such as compliance‑aware prompt engineering, document generation, objection response automation, synthetic data generation for low-frequency events, and customer sentiment modeling from surveys, call transcripts, or inspection notes.
• Experience working within enterprise AI governance frameworks, aligning conversational AI and analytics solutions with compliance, privacy, documentation, and ethical standards.