IND Applied AI Scientist

The Hartford; Hyderabad; On-site; INR 1,500,000 - 3,500,000; Full time

Job summary

The Hartford in Hyderabad is seeking an IND Staff Engineer to advance statistical modeling and ML using Python, pandas, NumPy, and scikit-learn, with strong SQL. Familiarity with PyTorch and TensorFlow is preferred as you work across the end-to-end modeling lifecycle.

You will design and productionize models, implement monitoring, handle NLP/GenAI tasks, and collaborate with teams to translate analytics into measurable business impact within an enterprise insurance context.

Qualifications

• 3+ years of experience applying deep learning in real-world use cases.
• Experience with NLP, embeddings, and GenAI capabilities.
• Experience deploying models and integrating scoring logic in production.
• Experience with cloud-based AI platforms (Vertex AI, SageMaker, Bedrock, Azure AI Services).
• Experience working with unstructured data, OCR, and PII considerations.
• Experience communicating modeling decisions to technical and non-technical audiences.

Skills

Python

pandas

NumPy

scikit-learn

SQL

PyTorch

TensorFlow

Deep learning

NLP

GenAI

Tools

Git

Unix

Docker

Kubernetes

Cloud platforms

Job description

IND Staff Engineer - GCC094

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.

Experience in statistical modeling and machine learning using Python, including extensive use of pandas, NumPy, scikit-learn, and strong SQL for data exploration, feature development, and knowledge preparation; familiarity with PyTorch and/or TensorFlow preferred. Experience across the end‑to‑end modeling lifecycle, including problem framing and requirements gathering, experiment design, offline evaluation, and ongoing production validation and monitoring. Solid understanding and practical application of core machine learning methods, with 3+ years of experience applying deep learning architectures in real‑world use cases. Experience designing and operationalizing model evaluation and monitoring approaches, including test set creation (gold and/or synthetic), metric definition and tracking (e.g., classification, forecasting, ranking/IR, and business KPIs), and supporting A/B testing, drift detection, and performance regression monitoring. Experience working with unstructured data, including document parsing and OCR fundamentals, text normalization, metadata and lineage awareness, and PII detection or redaction considerations. Experience using Git and Unix‑based development environments, with experience building reproducible notebooks or pipelines and ensuring repeatable analytical workflows; 3+ years of exposure to basic container and cloud fundamentals supporting deployment workflows. Experience communicating modeling decisions, design tradeoffs, evaluation results, and risks to both technical and non‑technical audiences, and translating analytical outcomes into measurable business impact. Experience working with cloud‑based AI platforms such as Google Vertex AI, AWS SageMaker or Bedrock, or Azure AI Services, supporting experimentation, model training, and deployment. Experience deploying models and integrating scoring logic into production systems, including operation within complex enterprise or packaged application environments (e.g., Duck Creek, Ratabase). Experience with NLP and Generative AI capabilities, including embeddings, retrieval strategies (dense and hybrid), chunking approaches, prompt engineering, structured outputs, and contributing to Retrieval‑Augmented Generation (RAG) solutions and evaluations. Experience or exposure to advanced GenAI applications and extensions, such as agent or tool‑use concepts, domain‑specific knowledge graph integration, synthetic data generation, sentiment modeling, and GenAI use cases in filing or compliance contexts. Experience working within enterprise AI governance expectations, including aligning model development with compliance, privacy, documentation, and ethical standards.

About Us | Our Culture | What It’s Like to Work Here

Every day, a day to do right. Showing up for people isn't just what we do. It's who we are - and have been for more than 200 years. We're devoted to finding innovative ways to serve our customers, communities and employees - continually asking ourselves what more we can do. Is our policy language as simple and inclusive as it can be? Can we better help businesses navigate our ever‑changing world? What else can we do to destigmatize mental health in the workplace? Can we make our communities more equitable? That we can rise to the challenge of these questions is due in no small part to our company values that our employees have shaped and defined. And while how we contribute looks different for each of us, it's these values that drive all of us to do more and to do better every day.