Senior Data Scientist

At Iron Mountain we know that work, when done well, makes a positive impact for our customers, our employees, and our planet. That’s why we need smart, committed people to join us. Whether you’re looking to start your career or make a change, talk to us and see how you can elevate the power of your work at Iron Mountain.

We provide expert, sustainable solutions in records and information management, digital transformation services, data centers, asset lifecycle management, and fine art storage, handling, and logistics. We proudly partner every day with our 225,000 customers around the world to preserve their invaluable artifacts, extract more from their inventory, and protect their data privacy in innovative and socially responsible ways. 

Are you curious about being part of our growth stor​y while evolving your skills in a culture that will welcome your unique contributions? If so, let's start the conversation.

Location: Bengaluru, India

Function: Enterprise Insights & Analytics | Global Business Services

Reports to: Manager – Analytics

Works closely with: Reporting Teams, Data Engineers, Functional Stakeholders (Care, Commercial, Operations, Finance, Procurement)

We are seeking a highly experienced Senior Data Scientist who can both lead by example and serve as a functional bridge between business needs and advanced analytics. This role will be instrumental in building scalable data science solutions on Google Cloud Platform (GCP) and will mentor junior data scientists across varied domains such as Care, Commercial, Operations, Finance, and Procurement.

This is a dual-role requiring strong modeling and engineering skills, as well as the ability to contextualize insights for business impact.

• Lead the design and development of ML models (predictive, prescriptive, and classification) using Python, TensorFlow, and Vertex AI

• Translate complex business problems into analytical solutions across commercial, care, operations, finance, and procurement domains

• Partner with functional teams to gather requirements, define use cases, and create KPIs aligned with business goals

• Guide and mentor junior data scientists on technical problem-solving, model development, and business storytelling

• Drive end-to-end model development and deployment pipelines using BigQuery, Vertex AI Workbench, GCS, and other GCP-native services

• Collaborate with Data Engineers to ensure data pipelines are robust, scalable, and efficient

• Participate in code reviews, model validations, and production tuning, ensuring reusability and consistency

• Communicate results effectively through dashboards, model explainability tools, or structured insight narratives

• Continuously evaluate and recommend new technologies or techniques that enhance model performance and delivery timelines

• Strong programming skills in Python, including use of packages like Pandas, NumPy, Scikit-learn, and TensorFlow/Keras

• Deep experience with Google Cloud Platform (GCP) including:

  • BigQuery for handling large-scale datasets

  • Vertex AI for building, training, and serving models

  • Cloud Storage, DataFlow, and Workflows for data orchestration

• Experience integrating ML pipelines with reporting tools such as Looker Studio or Tableau

• Solid data engineering mindset – able to optimize data pipelines, feature stores, and model training data for scale

• Demonstrated ability to work closely with functional leaders across Care, Commercial, Finance, and Ops to translate analytical outputs into business decisions

• Prior experience managing or mentoring a team of data scientists

• Strong stakeholder engagement and communication skills – both written and verbal

• High attention to detail and ability to manage ambiguity in business problems

• A structured approach to problem-solving and performance-driven mindset

• 5–8 years of experience in data science roles with at least 2 years in a senior or lead capacity

• Bachelor’s or Master’s in Data Science, Computer Science, Statistics, or related fields

• Proven track record of deploying models to production and generating measurable impact

• Experience working in a global or shared services (GBS) environment is a plus

• Technical Leadership & Mentorship

• Functional Fluency across Business Domains

• Data Engineering & MLOps Excellence

• Business Communication & Storytelling

• Model Governance & Reusability