Applied AI Data Scientist

🕒 Junho 9

🦌 Connecticut, Illinois, +2 estados a mais – Remoto

🦌 Connecticut – Remote 🌽 Illinois – Remote 🌲 North Carolina – Remote 🏈 Ohio – Remote

💵 $90.160 - $135.240 / ano

⏰ Tempo Integral

🟡 Pleno

🟠 Sênior

📊 Cientista de Dados

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The Hartford

SiteLinkedInTodas as Vagas

10.000+ funcionários

Fundada em 1810

💸 Finanças

👥 B2C

Insurance • Finance • B2C

A The Hartford é uma empresa de seguros bem estabelecida que oferece uma variedade de produtos, incluindo seguros de automóveis, residências e empresariais. Com mais de 200 anos de experiência, atende tanto a indivíduos quanto a pequenas e médias empresas, proporcionando soluções de seguros sob medida e benefícios para funcionários. A empresa é particularmente conhecida por seus programas de seguro de automóveis e residências endossados pela AARP, que oferecem benefícios e descontos exclusivos para membros.

Descrição

• Build and optimize ML, deep learning, and GenAI models using modern frameworks (PyTorch, TensorFlow, scikit-learn). • Design and deliver RAG pipelines, hybrid retrieval systems, and vector-based search workflows. • Develop Agentic AI solutions including tool orchestration, reasoning flows, and safe-execution strategies. • Run structured experimentation using evaluation metrics (BERTScore, BLEURT, semantic similarity, retrieval precision/recall). • Integrate solutions into GCP (Vertex AI, Workbench, Vector Search) and AWS (SageMaker, Bedrock). • Build ingestion, enrichment, and semantic retrieval flows for high-quality knowledge and feature engineering. • Partner with onshore and offshore DS/ML engineers to ensure quality, consistency, and shared technical patterns.

🎯 Requisitos

• 3–5+ years in Data Science, ML Engineering, Applied AI, or GenAI roles. • Strong Python and SQL skills; experience with deep learning and ML libraries. • Hands-on experience building RAG systems, vector search pipelines, and GenAI applications. • Familiarity with modern LLM platforms (Vertex AI, OpenAI, Bedrock, Azure OpenAI). • Experience implementing evaluation methodologies for both ML and GenAI. • Ability to translate ambiguous business problems into well-structured ML/GenAI solutions. • Experience designing multi-step agent workflows and reasoning pipelines. • Strong grounding in statistics, experiment design, and feature engineering. • Ability to present complex concepts clearly to technical and business stakeholders. • Comfortable working with agile teams and collaborating across time zones. • Experience partnering with SMEs to validate and refine AI outputs. • Experience with Snowflake or enterprise data platforms (preferred). • Insurance domain knowledge (underwriting, claims, or risk analysis) (preferred). • Experience with multimodal LLMs or enterprise prompt/agent frameworks (preferred).

🏖️ Benefícios

• Health insurance • 401(k) matching • Flexible working hours • Paid time off • Professional development opportunities • Short-term or annual bonuses • Long-term incentives • On-the-spot recognition