AI Engineer / Data Scientist, AI Experienced Associate

PwC•Washington, DC

2d•$63,000 - $141,500•Remote

About The Position

As part of the AI Engineering team within the Digital Assurance & Technology team, you will leverage advanced technologies and techniques to design and develop robust data solutions for clients. Within our Assurance practice, you will transform raw data into actionable insights, enabling informed decision-making and driving business growth. Your role will involve designing AI systems, data wrangling, and software implementation to enable AI models to be useful and scalable. You will support workstreams involving testing and evaluation of AI-enabled systems, analyze technical evidence and control effectiveness, and develop reusable tools that support responsible, reliable AI deployment. As an Associate, you will focus on learning and contributing to client engagement and projects while developing your skills and knowledge to deliver quality work. You will be exposed to clients to learn how to build meaningful client connections, manage and inspire others, and grow your personal brand by deepening your technical knowledge of firm services and technology resources. You will be expected to anticipate the needs of your teams and clients, embrace ambiguity, ask questions, and use these challenges as opportunities for growth. In this role, you will apply a learning mindset, take ownership of your development, and consistently deliver quality work that drives value for our clients and success as a team.

Requirements

At least a Bachelor's degree
At least 1 year of experience

Nice To Haves

Preference for at least one of the following fields of study: Analytics/Data Science, Artificial Intelligence/Robotics, Computer Science/Information Systems, Engineering
Demonstrating proficiency in Python and programming languages for AI solutions
Applying complex data analysis and pattern recognition to drive insights
Excelling in teamwork and collaboration within fast-paced environments
Testing, debugging, and documenting AI-enabled systems to support reliable solution performance.
Evaluating failure modes, bias, drift, hallucinations, explainability, and guardrails using established methods.
Measuring and communicating technical outcomes using defined metrics and evaluation approaches.
Translating technical findings and limitations into clear insights for clients and non-technical stakeholders.

Responsibilities

Designing and implementing AI systems to transform raw data into actionable insights
Developing and deploying machine learning models to support client decision-making
Collaborating with team members to integrate AI solutions into existing data infrastructure
Conducting complex data analysis to identify patterns and trends
Utilizing programming languages such as Python to build scalable AI applications
Applying data modeling techniques to enhance data quality and integration
Engaging in data wrangling and preprocessing to prepare datasets for analysis
Building and maintaining relational database management systems for efficient data storage
Supporting client engagements by providing technical insights and recommendations
Continuously learning and adapting to new AI technologies and methodologies
Supporting the design and execution of tests for AI-system behavior, performance, robustness, bias, explainability, and failure modes
Evaluating technical controls and evidence and clearly documenting findings, limitations, and recommendations
Developing reusable evaluation tools, automated tests, reference datasets, monitoring capabilities, and evidence workflows