Applied AI Data Scientist - Hybrid, Production ML & Impact

DLA Piper; Houston (TX); Híbrido; USD 130.000 - 206.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Medical, dental, and vision insurance

401(k) retirement plan

Descripción de la vacante

DLA Piper seeks a Data Scientist, Applied AI Solutions to collect, explore, and analyze large datasets to improve business and client outcomes. The role designs and deploys data models, algorithms, and machine learning solutions; performs custom analyses; and translates business, legal, and regulatory requirements into practical analytic approaches.

The position also develops and applies algorithmic testing methods to evaluate AI systems and tools, including bias and accuracy.

Formación

• Bachelor’s degree in a relevant field.
• Experience delivering revenue-generating client solutions.
• Hands-on ML with Python/SQL in enterprise settings.

Responsabilidades

• Develops and applies algorithmic testing methods to evaluate AI systems, models, and tools for bias, accuracy, reliability, robustness, and performance.
• Creates novel testing techniques, metrics, and evaluation frameworks for emerging AI systems and risks when established methods are insufficient.
• Translates legal, regulatory, and business requirements into analytic objectives, testable criteria, data specifications, and practical technical solutions.
• Works with internal stakeholders, lawyers, and clients to identify opportunities to leverage data to address needs.
• Prioritizes, scopes, and manages multiple data science projects with accountability for delivery quality and outcomes.

Conocimientos

Python

SQL

Machine Learning

Data Analysis

Communication

Data Visualization

Azure

Jupyter

Big Data

Educación

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

Herramientas

Python

R

SQL

SAS

NLTK

Scikit-Learn

Excel

Tableau

Power BI

Jupyter

Azure

Descripción del empleo

DLA Piper seeks a Data Scientist, Applied AI Solutions to collect, explore, and analyze large datasets to improve business and client outcomes. The role designs and deploys data models, algorithms, and machine learning solutions; performs custom analyses; and translates business, legal, and regulatory requirements into practical analytic approaches.

The position also develops and applies algorithmic testing methods to evaluate AI systems and tools, including bias and accuracy.