AI Data Scientist

Iwana Labs; United States; Remote; USD 99,000 - 143,000; Full time

Benefits offered by this job

Paid time off 22 days

Meal allowance

Private health insurance

Learning budget

Mac computer provided

Job summary

Iwana Labs is seeking a hands-on consultant to bridge data science, machine learning, experimentation, and generative AI for a major media client. You will identify high-value opportunities, design fit-for-purpose solutions, and shepherd them from scoping to production deployment, with personalization and AI-powered automation at the core.

The role emphasizes partnering with client teams, building scalable data pipelines, and ensuring robust evaluation, monitoring, and governance of AI-enabled

Qualifications

• Strong engineering foundations and experience operating production systems.
• Practical work across data science, machine learning, experimentation, and generative AI.
• Ability to design and interpret experiments with appropriate statistical rigour.
• Comfort translating business questions into technical designs and communicating trade-offs to mixed audiences.
• Ability to learn new platforms and tools quickly; familiarity with a specific stack is less important than adaptability.

Responsibilities

• Develop personalization, recommendation, ranking, segmentation, and next-best-action models using behavioural, content, and contextual signals.
• Design and analyse A/B tests, including hypotheses, success metrics, guardrails, sample-size planning, and decision criteria.
• Build machine learning models and analytical solutions tied to measurable product and business outcomes.
• Create generative AI applications such as retrieval-augmented generation, semantic search, tool-calling workflows, and AI agents.
• Construct the data pipelines, APIs, and services that take AI capabilities into production.
• Evaluate solutions for model quality, business impact, reliability, latency, security, and cost, and implement monitoring, validation, fallbacks, access controls, and human approval steps.

Skills

Data science

Machine learning

Experimentation

Generative AI

Production systems

Job description

Role overview

A hands-on consultancy role spanning data science, machine learning, experimentation, and generative AI. The position partners directly with client teams to identify high-value opportunities, design fit-for-purpose solutions, and carry them from early scoping through to production deployment. The initial engagement is with a major media company, where the focus is on personalization, experimentation, and AI-powered automation.

Responsibilities

• Develop personalization, recommendation, ranking, segmentation, and next-best-action models using behavioural, content, and contextual signals.
• Design and analyse A/B tests, including hypotheses, success metrics, guardrails, sample-size planning, and decision criteria.
• Build machine learning models and analytical solutions tied to measurable product and business outcomes.
• Create generative AI applications such as retrieval-augmented generation, semantic search, tool-calling workflows, and AI agents.
• Construct the data pipelines, APIs, and services that take AI capabilities into production.
• Evaluate solutions for model quality, business impact, reliability, latency, security, and cost, and implement monitoring, validation, fallbacks, access controls, and human approval steps.

Requirements

• Strong engineering foundations and experience operating production systems.
• Practical work across data science, machine learning, experimentation, and generative AI.
• Ability to design and interpret experiments with appropriate statistical rigour.
• Comfort translating business questions into technical designs and communicating trade-offs to mixed audiences.
• Ability to learn new platforms and tools quickly; familiarity with a specific stack is less important than adaptability.

Benefits and work setup

Remote-first anywhere in Spain, with the team gathering in person a few times a year. Twenty-two days of paid time off plus public holidays, a meal allowance, and private health insurance. A learning budget covers conferences, courses, and books, and a Mac plus the rest of the workstation is provided. Access to current AI agents and tooling is included so the practitioner can work efficiently.