Commercial Data Scientist – AI & Growth with Flexible Work

Iron Mountain; Yumbo; Hybrid; COP 120,000,000 - 180,000,000; Full time

Benefits offered by this job

Competitive compensation and benefits

Flexible work options

Health, wellness, and retirement plans

Continuous learning and growth

Job summary

Iron Mountain is seeking an analytical Commercial Data Scientist to join our Global Marketing team. You will transform raw data streams into actionable intelligence for customer, market, and competitive programs, and build analytics like CLV and account health scoring to guide business decisions.

The role requires 5+ years in data analysis or data science, strong knowledge of Python or R, SQL, and visualization tools, plus familiarity with AI frameworks to automate insights and support CX

Qualifications

• 5+ years of experience in a data analysis or data science role, preferably within a large enterprise or B2B tech environment.

Responsibilities

• Lead technical data execution: Transform raw first- and third-party data streams into usable intelligence across customer, market, and competitive programs.
• Develop and maintain commercial models: Build and manage analytics programs including Customer Lifetime Value (CLV), Account Health scoring, and Propensity to Buy.
• Deploy AI and generative tools: Implement advanced machine learning techniques, LLM orchestration, and RAG architectures to build intelligent agents and automate business insights.
• Synthesize actionable insights: Translate complex analytical findings into intuitive dashboards and reports using tools like Tableau, Power BI, or Looker.

Skills

Data analysis

Customer experience

Market research

Competitive intelligence

Tools

Python

R

SQL

Tableau

Power BI

Looker

LangChain

LlamaIndex

Vertex AI

Job description

Iron Mountain is seeking an analytical Commercial Data Scientist to join our Global Marketing team. You will transform raw data streams into actionable intelligence for customer, market, and competitive programs, and build analytics like CLV and account health scoring to guide business decisions.

The role requires 5+ years in data analysis or data science, strong knowledge of Python or R, SQL, and visualization tools, plus familiarity with AI frameworks to automate insights and support CX