Data Scientist, AI for CX & Trust (Hybrid)

Unchain Data; Menlo Park, Northern (CA, KY); Hybrid; USD 158,000 - 185,000; Full time

Benefits offered by this job

Bonus programs

Equity ownership

401(k) matching

Best-in-class health insurance

Job summary

Robinhood is seeking a Data Scientist, Agentic (CX) to lead ML development across the customer experience stack. You will own experimentation through deployment, building models for support, personalization, and safe, scalable interactions with customers.

The role requires collaboration with product and engineering, with in-person presence in Menlo Park, CA and New York, NY at least 3 days per week; strong Python and SQL skills are essential for end-to-end ML systems.

Qualifications

• Strong Python and SQL skills with end-to-end ML systems experience.
• Experience with agent-based AI systems, including reasoning loops, tool use, memory, and orchestration.
• Experience designing experiments and applying causal inference methods, including A/B testing.
• Ability to work through ambiguous problems and collaborate with product and engineering teams.

Responsibilities

• Build and deploy ML models for customer support systems, including intent classification, escalation detection, and multi-agent orchestration.
• Design evaluation frameworks using LLM-based review methods, human feedback loops, and automated quality metrics.
• Develop propensity, segmentation, and personalization models for proactive outreach and tailored AI experiences.
• Translate advances in agent architectures into production systems, collaborating with engineering on prompts, retrieval, memory, and orchestration.
• Maintain scalable, high-quality response systems in collaboration with product, engineering, legal, and compliance teams.

Skills

Python

SQL

ML end-to-end

Agent-based AI

Job description

Robinhood is seeking a Data Scientist, Agentic (CX) to lead ML development across the customer experience stack. You will own experimentation through deployment, building models for support, personalization, and safe, scalable interactions with customers.

The role requires collaboration with product and engineering, with in-person presence in Menlo Park, CA and New York, NY at least 3 days per week; strong Python and SQL skills are essential for end-to-end ML systems.