Senior Data Scientist

TL;DR

Senior Data Scientist (AI/SaaS): Developing and improving dynamic pricing algorithms and machine learning models for short-term rental revenue management with an accent on AI integration, statistical modeling, and scalable data pipelines. Focus on designing and deploying modern AI technologies, driving measurable product impact, and mentoring data science practices.

Location: Remote, must be located in Brazil or Peru

Company

hirify.global powers short-term rental businesses with a leading Revenue Management System, leveraging AI and modern technologies to optimize revenue for property managers worldwide.

What you will do

• Collaborate cross-functionally to deliver on dynamic pricing recommendations and analysis aligned with product vision.
• Design, build, test, and maintain scalable data pipelines and ML solutions with data engineers.
• Apply modern AI technologies such as RAG, MCP, embedding-based semantic search, and LangChain for internal tooling and customer-facing intelligence.
• Integrate observability, monitoring, and human feedback into ML pipelines to improve model performance.
• Prototype and ship LLM-powered assistants and automations to enhance customer decision-making.
• Mentor data scientists and promote best practices in experimentation, validation, and interpretability.

Requirements

• Must be located in Brazil or Peru
• 5+ years as a Data Scientist and 10+ years in SaaS, preferably in high-scale platforms.
• Proven expertise in machine learning, statistical modeling, and delivering impactful models.
• Fluency in Python and data science tools like pandas, numpy, scikit-learn, Spark, SQL, and Streamlit.
• Strong product orientation and experimental mindset with causal inference experience.
• Experience with modern AI techniques and tooling is a plus.

Nice to have

• Experience in revenue management, dynamic pricing, or short-term rental industry.

Culture & Benefits

• Stock options, unlimited PTO, private health insurance, and more benefits.
• Commitment to diversity, equity, and inclusion.
• Values-driven culture emphasizing care, trust, curiosity, and teamwork.

Hiring process

• Video conversation with recruiting team.
• Hiring manager interview.
• Skills assessment and peer/technical interviews.
• VP of Engineering interview.