[Remote] Applied AI Data Scientist
Note: The job is a remote job and is open to candidates in USA. The Hartford is an insurance company dedicated to making a difference and expanding its Data Science, AI & Analytics capabilities. They are seeking an Applied AI Data Scientist to design, build, evaluate, and operationalize enterprise-grade AI systems, collaborating with various teams to drive business impact through innovative ML and GenAI solutions.
Responsibilities
- 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
Skills
- 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
- 5+ years with Bachelor's degree; less for Master's
- Candidate must be authorized to work in the US without company sponsorship
- Experience with Snowflake or enterprise data platforms
- Insurance domain knowledge (underwriting, claims, or risk analysis)
- Experience with multimodal LLMs or enterprise prompt/agent frameworks
- Master's preferred in Machine Learning, Applied Math, Data Science, Computer Science, or related fields
Benefits
- Other rewards may include short-term or annual bonuses
- Long-term incentives
- On-the-spot recognition
Company Overview