AI Engineer / Data Scientist, AI Senior Associate

PricewaterhouseCoopers•Stamford, NY

1d•Onsite

About The Position

As part of the AI Engineering team within the Digital Assurance & Technology team, you will play a pivotal role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Within our Assurance practice, you will focus on developing and implementing advanced AI and machine learning solutions to drive innovation and enhance business processes. Your work will involve designing and optimizing algorithms, models, and systems to enable intelligent decision-making and automation. You will independently own workstreams involving lead testing and evaluation of AI-enabled systems, analyze technical evidence and control effectiveness, and develop reusable tools that support responsible, reliable AI deployment. As a Senior Associate, you will build meaningful client connections and learn how to manage and inspire others. You will navigate increasingly complex situations, growing your personal brand and deepening your technical skills. You are expected to anticipate the needs of your teams and clients, delivering quality work while embracing increased ambiguity. In this role at PwC, you will use a broad range of tools, methodologies, and techniques to generate new ideas and solve problems, interpreting data to inform insights and recommendations. You will uphold professional and technical standards, contributing to the firm's overall business strategies and client solutions.

Requirements

At least a Bachelor's degree
At least 2 years 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 AI implementation and complex data analysis
Utilizing programming languages such as Python for data modeling
Excelling in machine learning and deep learning techniques
Integrating data infrastructure and quality management in projects
Owning production AI systems across deployment, monitoring, evaluation, and incident response
Evaluating failure modes, bias, drift, hallucinations, explainability, and guardrails
Guiding architecture trade-offs to deliver measurable, defensible outcomes
Measuring and communicating technical and business outcomes using defined methods
Translating technical findings and limitations for clients and non-technical stakeholders
Mentoring junior team members

Responsibilities

Designing and optimizing AI and machine learning algorithms to enhance business processes and drive innovation
Transforming raw data into actionable insights to support informed decision-making and business growth
Developing and implementing advanced AI solutions using programming languages such as Python
Building and maintaining data infrastructure and integration systems to support complex data analysis
Utilizing data modeling techniques to improve data quality and reliability
Collaborating with teams to develop and deploy speech recognition algorithms and natural language processing tools
Upholding professional and technical standards in line with the firm's code of conduct and independence requirements
Navigating complex situations to anticipate client needs and deliver quality solutions
Independently designing and executing tests for AI-system behavior, performance, robustness, bias, explainability, and failure modes.
Evaluating technical controls and evidence and clearly document findings, limitations, and recommendations.
Building reusable evaluation tools, automated tests, reference datasets, monitoring capabilities, and evidence workflows