AI Enablement Data Scientist — Internal Solutions

HDR, Inc.; Baltimore (MD); On-site; USD 150,000 - 215,000; Full time

Job summary

HDR, Inc. seeks an Applied Data Scientist – AI Enablement to build internal AI capabilities for HDR’s Transportation Business Group, developing AI solutions and scalable data pipelines.

The role focuses on removing bottlenecks and preparing foundations for scale. As capabilities mature, responsibilities will broaden to client-facing AI delivery and advisory work, leveraging proven solutions as repeatable services across cloud environments (Azure, AWS, GCP).

Qualifications

• Bachelor’s degree in a closely related field or equivalent experience.
• 3+ years with data engineering tools and languages such as SQL, Power Query, and Pandas.
• 3+ years with BI tools like Power BI, Tableau, Plotly, Seaborn, and Matplotlib.
• 3+ years in data science languages such as Python and R.
• Experience with cloud data pipelines and production ML deployments.
• Strong writing and communication abilities.
• Six Sigma or process improvement certifications are a plus.

Responsibilities

• Design, develop, and deploy AI solutions for internal transportation needs.
• Build reusable AI components and data pipelines for future client delivery.
• Manage full ML model lifecycle: development, deployment, monitoring, retraining, and inference.
• Identify data, tooling, governance, and process bottlenecks to scale AI capacity.
• Collaborate with IT, data architects, and stakeholders to propose scalable improvements.
• Support future client pursuits and contribute to repeatable AI services.

Skills

Analytical skills

Communication skills

Written communication

Education

Bachelor’s degree in a closely related field

Advanced Degree

Tools

Azure

AWS

GCP

Power BI

Tableau

Python

R

SQL

Power Query

Pandas

Plotly

Seaborn

Matplotlib

Job description

HDR, Inc. seeks an Applied Data Scientist – AI Enablement to build internal AI capabilities for HDR’s Transportation Business Group, developing AI solutions and scalable data pipelines.

The role focuses on removing bottlenecks and preparing foundations for scale. As capabilities mature, responsibilities will broaden to client-facing AI delivery and advisory work, leveraging proven solutions as repeatable services across cloud environments (Azure, AWS, GCP).