Applied Data Scientist: AI Enablement & Internal Solutions

HDR, Inc.; New York (NY); On-site; USD 150,000 - 215,000; Full time

Job summary

HDR, Inc. is seeking an Applied Data Scientist – AI Enablement to drive internal AI capabilities and scalable data solutions across our Transportation Business Group.

The role starts with internal solution development, data foundation improvements, and bottleneck removal, with future client-facing advisory work as capabilities mature. The role emphasizes collaboration with IT, data architects, and business stakeholders, plus design of reusable components, governance, and processes to scale AI

Qualifications

• Minimum 3 years experience with data engineering tools and languages (SQL, Power Query, Pandas).
• Minimum 3 years experience with BI tools (Power BI, Tableau, Plotly, Seaborn, Matplotlib).
• Minimum 3 years experience with data science languages (Python, R).
• Experience managing end-to-end data science projects and model lifecycles.
• Strong writing, communication and organizational skills.

Responsibilities

• Design, develop, and deploy AI solutions addressing internal transportation business needs.
• Build reusable AI components, data pipelines, and scalable workflows.
• Manage full model lifecycle including development, deployment, monitoring, drift detection, retraining, and inference.

Skills

SQL

Power Query

Pandas

Power BI

Tableau

Plotly

Seaborn

Matplotlib

Python

R

Cloud platforms

Data pipelines

Model lifecycle

Education

Bachelor’s degree in a closely related field

Advanced Degree

Tools

Azure

AWS

GCP

Job description

HDR, Inc. is seeking an Applied Data Scientist – AI Enablement to drive internal AI capabilities and scalable data solutions across our Transportation Business Group.

The role starts with internal solution development, data foundation improvements, and bottleneck removal, with future client-facing advisory work as capabilities mature. The role emphasizes collaboration with IT, data architects, and business stakeholders, plus design of reusable components, governance, and processes to scale AI