Managed Services - Data & Analytics -AI QE Analyst

s maximize the value of their investment focusing on continuous improvement of their analytics solutions such as Microsoft, Amazon Web Services and Google Cloud.

To really stand out and make us fit for the future in a constantly changing world, each and every one of us at PwC needs to be a purpose-led and values-driven leader at every level. To help us achieve this we have the PwC Professional; our global leadership development framework. It gives us a single set of expectations across our lines, geographies and career paths, and provides transparency on the skills we need as individuals to be successful and progress in our careers, now and in the future.

As a Manager, you'll work as part of a team of problem solvers, helping to solve complex business issues from strategy to execution. PwC Professional skills and responsibilities for this management level include but are not limited to:

• Develop new skills outside of comfort zone.

• Act to resolve issues which prevent the team working effectively.

• Coach others, recognise their strengths, and encourage them to take ownership of their personal development.

• Analyse complex ideas or proposals and build a range of meaningful recommendations.

• Use multiple sources of information including broader stakeholder views to develop solutions and recommendations.

• Address sub-standard work or work that does not meet firm's/client's expectations.

• Use data and insights to inform conclusions and support decision-making.

• Develop a point of view on key global trends, and how they impact clients.

• Manage a variety of viewpoints to build consensus and create positive outcomes for all parties.

• Simplify complex messages, highlighting and summarising key points.

• Uphold the firm's code of ethics and business conduct.

****Job Requirements and Preferences:

Basic Qualifications:

Minimum Degree Required:
Bachelor Degree

Required Fields of Study:
Mathematics, Computer and Information Science, Management Information Systems

Minimum Years of Experience:
5 year(s)

Preferred Qualifications:

Preferred Knowledge/Skills:****

Demonstrates extensive abilities and/or a proven record of success as a team leader:

• Performing statistical tests on large datasets to determine data quality and integrity;

• Evaluating system performance and design, as well as its effect on data quality;

• Collaborating with database developers to improve data collection and storage processes;

• Running data queries to identify coding issues and data exceptions, as well as cleaning data;

• Gathering data from primary or secondary data sources to identify and interpret trends;

• Reporting data analysis findings to management to inform business decisions and prioritize information system needs;

• Documenting processes and maintaining data records;

• Adhering to industry standard practices in data analysis and collection;

• Keeping abreast of developments and trends in data quality analysis;

• Performing triage, resolving tickets, and managing SLAs by implementing break-fixes;

• Implementing permanent solution by performing Root Cause Analysis (RCA) of the incidents;

• Reviewing existing solutions, identify opportunities for continuous improvements, and perform enhancements to systems;

• Using feedback and reflection to develop self-awareness, personal strengths, and address development areas;

• Demonstrating critical thinking and the ability to bring order to unstructured problems;

• Communicating effectively and work in a team environment that includes client interactions, workstream management, and cross-team collaboration;

• Understanding escalation/risk management; and,

• Willing to work in shifts, provide hand-over to global teams, and provide on-call support during off-business hours.

• Design and execute tests to identify bugs, biases, and performance issues in AI models.

• Understand specific algorithms involved and craft test cases that expose potential weaknesses.

• Analyze datasets for biases, inconsistencies, and missing information that could negatively impact the AI's performance.

• Work closely with engineers and data scientists to integrate quality assurance practices throughout the AI development lifecycle.

• Leverage understanding of AI and quality engineering principles to design metrics and analyze data to identify areas for improvement and potential risks.

Learn more about how we work: https://pwc.to/how-we-work

PwC does not intend to hire experienced or entry level job seekers who will need, now or in the future, PwC sponsorship through the H-1B lottery, except as set forth within the following policy: https://pwc.to/H-1B-Lottery-Policy.

All qualified applicants will receive consideration for employment at PwC without regard to race; creed; color; religion; national origin; sex; age; disability; sexual orientation; gender identity or expression; genetic predisposition or carrier status; veteran, marital, or citizenship status; or any other status protected by law. PwC is proud to be an affirmative action and equal opportunity employer.

For positions in California, Colorado, Hawaii, Nevada, New York State, or Washington State, or for opportunities that will report to a supervisor, office or other work site in New York State, please visit the following link for pay range information: https://pwc.to/payrange-v1-mgdsrvcsseniorassociate