Sr. Insights Analyst

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.

Job Summary

We are seeking a Data Analytics & AI Business Analyst to join our dynamic and innovative team. The successful candidate will act as a critical bridge between business stakeholders and technical teams to drive the successful implementation of data analytics and AI-driven solutions that enhance decision-making and improve business outcomes. This role involves gathering business requirements, identifying data-driven opportunities, and supporting the development of AI and analytics models that solve complex business problems.

The ideal candidate will have a strong foundation in business analysis, data analytics, and an understanding of AI/ML concepts. They will work closely with cross-functional teams to ensure the successful delivery of analytics initiatives that align with business goals.

Key Responsibilities

1. Business Analysis & Requirement Gathering

• Collaborate with business stakeholders to understand and document business needs, challenges, and opportunities for data-driven solutions.

• Translate business requirements into data analytics and AI solution requirements that technical teams can implement.

• Identify key metrics, KPIs, and reporting requirements to measure the success of data-driven initiatives.

• Ensure business requirements are aligned with organizational data governance and compliance policies.

2. Data Analytics & AI Solution Delivery

• Work with data scientists, data engineers, and AI specialists to design, develop, and deploy analytics models and AI solutions that address business challenges.

• Support the end-to-end lifecycle of AI/ML projects, including requirement gathering, solution design, testing, deployment, and ongoing monitoring.

• Ensure data integrity and quality throughout the analytics pipeline, working closely with data teams to address any gaps or inconsistencies.

• Assist in the implementation of predictive analytics, machine learning models, and AI-based automation to enhance business processes.

3. Insights & Reporting

• Assist in developing interactive dashboards and reports using BI tools (e.g., Power BI, Tableau) to present actionable insights to stakeholders.

• Analyze and interpret complex datasets to identify trends, patterns, and business opportunities.

• Ensure that stakeholders can derive maximum value from analytics insights by providing training and support as needed.

4. Project Management & Stakeholder Communication

• Act as a liaison between business units and technical teams, ensuring effective communication throughout project lifecycles.

• Manage project timelines, deliverables, and risks to ensure timely delivery of data analytics and AI solutions.

• Prepare and present project updates, recommendations, and insights to senior management and stakeholders.

5. Continuous Improvement & Innovation

• Stay updated on emerging trends in AI, machine learning, and data analytics to identify new opportunities for innovation within the organization.

• Recommend best practices for data analytics and AI adoption to improve business processes and decision-making.

• Identify automation opportunities within business processes and support their implementation through AI/ML models.

Required Skills & Qualifications

Technical Skills:

• Strong understanding of data analytics tools and platforms (e.g., SQL, Python, R, Power BI, Tableau).

• Familiarity with AI/ML concepts, including predictive analytics, classification models, clustering, and natural language processing (NLP).

• Experience with data manipulation, data cleaning, and data visualization.

• Knowledge of data governance, data security, and compliance requirements.

• Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) for data and AI solutions is a plus.

Business Skills:

• Excellent business analysis and requirement gathering skills.

• Strong understanding of business processes and KPIs across different functions such as sales, marketing, customer service, and operations.

• Ability to translate business needs into technical requirements and bridge the gap between business and technical teams.

• Strong project management and organizational skills to manage multiple initiatives simultaneously.

Soft Skills:

• Strong communication and presentation skills to deliver insights and project updates to both technical and non-technical stakeholders.

• Ability to work collaboratively with cross-functional teams in a fast-paced environment.

• Strong problem-solving and critical-thinking skills.

• Proactive and curious mindset with a passion for continuous learning and innovation.

Education & Experience Requirements

• Bachelor’s degree in Data Analytics, Computer Science, Business Administration, or a related field.

• 6+ years of experience in a data analytics or business analyst role, preferably with exposure to AI/ML projects.

• Experience with BI tools (Power BI, Tableau) and data manipulation tools (SQL, Python, R).

• Experience working in agile project environments is a plus.

Key Performance Indicators (KPIs) for Success

• Timely and accurate delivery of data analytics and AI projects.

• Improvement in business KPIs through the implementation of data-driven solutions.

• Adoption and usage of AI/analytics insights by business stakeholders.

• Reduction in manual processes through AI-driven automation.

Continuous identification of new data-driven opportunities to improve business outcomes.

Category: Customer Support