Principal, Data Scientist

American Tower

1d

About The Position

The Team We are seeking a Principal Data Scientist to join American Tower’s Information Technology organization’s Data & Analytics team. The team drives the strategy, architecture, and delivery of advanced machine learning (ML) and artificial intelligence (AI) solutions across the enterprise. Day to day you will design and implement scalable ML systems, partner with the Data Engineering team on pipelines, and collaborate with the Productization & Adoption team to deploy models into production. As a Principal Data Scientist, you will set technical standards, mentor team members, and ensure solutions align with governance frameworks established by the Strategy & Governance team. Responsibilities What You Can Offer Us Partner with Operations, Finance, Sales, and Legal department stakeholders to translate complex problems into measurable AI and ML initiatives, influence the analytics roadmap, and communicate findings to technical and non-technical audiences. Act as lead technical consultant and subject matter expert for scoping AI projects, defining requirements, and ensuring high-quality deliveries of advanced solutions. Design and implement supervised, unsupervised, and reinforcement learning models, including feature engineering, model selection, and rigorous validation for accuracy and scalability. Architect solutions for unstructured data (contracts, documents, images), geospatial data, and enterprise systems (Salesforce customer resource management (“CRM”), Oracle Enterprise Resource Planning) to deliver actionable insights. Design and build end-to-end ML systems aligned with machine learning operations (“MLOps”) best practices; collaborate with the Data Engineering team on pipelines and with the Productization & Adoption team on deployments. Define and enforce standards for model governance, ethics, and bias detection in compliance with organizational policies. Mentor and guide Data Scientists, lead technical reviews, and recommend tools and methodologies to enhance the team’s capabilities and performance. Other duties as assigned. Qualifications What You Need to Succeed Bachelor’s degree required, with a concentration in Computer Science, Statistics, Engineering, Physics, or a related quantitative field preferred. Master’s degree or other advanced degree preferred. A minimum of 8 years of data science or machine learning experience with at least 5 years as a senior- or principal-level practitioner delivering models in production required. Expert proficiency in Python programming language and ML libraries (e.g., scikit-learn, TensorFlow, PyTorch). Strong foundation in statistics, causal inference, time series, and optimization with an ability to select appropriate methods for given problems. Deep expertise in computer vision or geospatial/geographic information system modeling. Experience with MLOps platforms and workflows (Databricks, MLflow, Azure ML, Amazon SageMaker, or Google Vertex AI), including experiment tracking and model registry. Experience deploying models to production systems (application programming interfaces, streaming, batch workflows) with appropriate monitoring and alerting. Familiarity with data platforms (Databricks or Snowflake) and enterprise systems (Salesforce CRM, Oracle Enterprise Resource Planning) preferred. Strong written and oral communication skills, including the ability to present ideas and suggestions clearly and effectively. Ability to work with different functional groups and levels of employees to effectively and professionally achieve results. Strong organizational skills; ability to accomplish multiple tasks within the agreed-upon timeframes through effective prioritization of duties and functions in a fast-paced environment.

Requirements

• Bachelor’s degree required, with a concentration in Computer Science, Statistics, Engineering, Physics, or a related quantitative field preferred.
• A minimum of 8 years of data science or machine learning experience with at least 5 years as a senior- or principal-level practitioner delivering models in production required.
• Expert proficiency in Python programming language and ML libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Strong foundation in statistics, causal inference, time series, and optimization with an ability to select appropriate methods for given problems.
• Deep expertise in computer vision or geospatial/geographic information system modeling.
• Experience with MLOps platforms and workflows (Databricks, MLflow, Azure ML, Amazon SageMaker, or Google Vertex AI), including experiment tracking and model registry.
• Experience deploying models to production systems (application programming interfaces, streaming, batch workflows) with appropriate monitoring and alerting.
• Strong written and oral communication skills, including the ability to present ideas and suggestions clearly and effectively.
• Ability to work with different functional groups and levels of employees to effectively and professionally achieve results.
• Strong organizational skills; ability to accomplish multiple tasks within the agreed-upon timeframes through effective prioritization of duties and functions in a fast-paced environment.

Nice To Haves

• Master’s degree or other advanced degree preferred.
• Familiarity with data platforms (Databricks or Snowflake) and enterprise systems (Salesforce CRM, Oracle Enterprise Resource Planning) preferred.

Responsibilities

• Partner with Operations, Finance, Sales, and Legal department stakeholders to translate complex problems into measurable AI and ML initiatives, influence the analytics roadmap, and communicate findings to technical and non-technical audiences.
• Act as lead technical consultant and subject matter expert for scoping AI projects, defining requirements, and ensuring high-quality deliveries of advanced solutions.
• Design and implement supervised, unsupervised, and reinforcement learning models, including feature engineering, model selection, and rigorous validation for accuracy and scalability.
• Architect solutions for unstructured data (contracts, documents, images), geospatial data, and enterprise systems (Salesforce customer resource management (“CRM”), Oracle Enterprise Resource Planning) to deliver actionable insights.
• Design and build end-to-end ML systems aligned with machine learning operations (“MLOps”) best practices; collaborate with the Data Engineering team on pipelines and with the Productization & Adoption team on deployments.
• Define and enforce standards for model governance, ethics, and bias detection in compliance with organizational policies.
• Mentor and guide Data Scientists, lead technical reviews, and recommend tools and methodologies to enhance the team’s capabilities and performance.
• Other duties as assigned.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal
• Number of Employees: 1,001-5,000 employees