Applied AI Data Scientist for Legal Tech Impact

DLA Piper; Minneapolis (MN); Hybrid; USD 130,000 - 206,000; Full time

Job summary

DLA Piper is seeking a Data Scientist, Applied AI Solutions to analyze large datasets, design and deploy ML models, and translate business and regulatory needs into practical analytic approaches. The role collaborates with lawyers, clients, and cross-functional teams to deliver data-driven solutions with measurable business impact.

You will work on bias and accuracy testing, model governance, and production pipelines, using Python, SQL, and Azure AI services in a hybrid U.S. office environment.

Qualifications

• Bachelor's degree in computer science, data science, statistics, applied mathematics or related field.
• Minimum 5 years of relevant experience applying data science and machine learning techniques to complex business problems.

Responsibilities

• Develops and applies algorithmic testing methods to evaluate AI systems for bias, accuracy, reliability, and performance.
• Translates legal, regulatory, and business requirements into analytic objectives, data specifications, and practical technical solutions.
• Designs, builds, deploys, and supports production machine learning models at scale.

Skills

Python

SQL

Machine learning

Data analysis

Azure

Agile methodologies

Communication

Model governance

Education

Bachelor's degree in computer science, data science, statistics, applied mathematics or related field

Tools

Python

SQL

SAS

NLTK

Scikit-Learn

Tableau

Power BI

Jupyter

Excel

Azure

Job description

DLA Piper is seeking a Data Scientist, Applied AI Solutions to analyze large datasets, design and deploy ML models, and translate business and regulatory needs into practical analytic approaches. The role collaborates with lawyers, clients, and cross-functional teams to deliver data-driven solutions with measurable business impact.

You will work on bias and accuracy testing, model governance, and production pipelines, using Python, SQL, and Azure AI services in a hybrid U.S. office environment.