Acceleration Center Financial Crimes Unit - Risk Architecture Experienced Associate, Software Engineer (Python/SQL)

Sorry, this job was removed at 07:17 p.m. (CST) on Friday, Dec 13, 2024
Pittsburgh, PA
Hybrid
66K-78K Annually
Internship
Artificial Intelligence • Professional Services • Business Intelligence • Consulting • Cybersecurity • Generative AI
At PwC, our purpose is to build trust in society and solve important problems.
The Role

At PwC, our people in data and analytics focus on leveraging data to drive insights and make informed business decisions. They utilise advanced analytics techniques to help clients optimise their operations and achieve their strategic goals. In data analysis at PwC, you will focus on utilising advanced analytical techniques to extract insights from large datasets and drive data-driven decision-making. You will leverage skills in data manipulation, visualisation, and statistical modelling to support clients in solving complex business problems.
Driven by curiosity, you are a reliable, contributing member of a team. In our fast-paced environment, you are expected to adapt to working with a variety of clients and team members, each presenting varying challenges and scope. Every experience is an opportunity to learn and grow. You are expected to take ownership and consistently deliver quality work that drives value for our clients and success as a team. As you navigate through the Firm, you build a brand for yourself, opening doors to more opportunities.
Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to:

  • Apply a learning mindset and take ownership for your own development.
  • Appreciate diverse perspectives, needs, and feelings of others.
  • Adopt habits to sustain high performance and develop your potential.
  • Actively listen, ask questions to check understanding, and clearly express ideas.
  • Seek, reflect, act on, and give feedback.
  • Gather information from a range of sources to analyse facts and discern patterns.
  • Commit to understanding how the business works and building commercial awareness.
  • Learn and apply professional and technical standards (e.g. refer to specific PwC tax and audit guidance), uphold the Firm's code of conduct and independence requirements.


As an Associate in our Risk Analytics and Modeling team, you'll have the opportunity to apply your quantitative, modeling and analytical skills in a real world environment to develop or validate statistical, financial engineering, and AI/machine learning models in the areas of credit risk, market risk, assets and liabilities management, fraud detection, anti money laundering and other functional modeling and analytics area.
Job Requirements and Preferences:
Basic Qualifications:
Minimum Degree Required:
Bachelor Degree
Minimum Years of Experience:
2 year(s)
Preferred Qualifications:
Preferred Fields of Study:
Economics, Statistics, Applied Mathematics, Mathematics, Financial Mathematics, Data Processing/Analytics/Science
Additional Educational Preferences:
Master Degree in Financial Engineering is also preferred.
Preferred Knowledge/Skills:
Demonstrates some abilities and/or a proven record of success in the implementation of Advanced Data Analytics and modeling that include:

  • Possessing experience with one or more of the following key programming and data analytics tools: Python, R, SAS;


  • Working knowledge of the following secondary languages and tools is a plus: Java, C++/C#, SQL, Tableau, Alteryx, and Excel Macros / VBA /JS;


  • Displaying understanding of advanced AI/machine learning, statistical/econometric modeling techniques, and financial engineering methods to develop and/or validate models (Masters-level coursework in at least one of these subject areas is preferred);


  • Demonstrating knowledge of the financial services industry;


  • Demonstrating exposure to modeling methodologies in at least one of the following areas: credit risk, market risk, assets and liabilities management, fraud detection, anti money laundering and other functional modeling and analytics areas; and,


  • Displaying knowledge or familiarity with industry financial instrument pricing tools and data sources e.g. Bloomberg, Refinitiv etc.


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.
The salary range for this position is: $66,000 - $78,000, plus individuals may be eligible for an annual discretionary bonus. For roles that are based in Maryland, this is the listed salary range for this position. Actual compensation within the range will be dependent upon the individual's skills, experience, qualifications and location, and applicable employment laws. PwC offers a wide range of benefits, including medical, dental, vision, 401k, holiday pay, vacation and more. To view our benefits at a glance, please visit the following link: https://pwc.to/benefits-at-a-glance

What the Team is Saying

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The Company
Richmond, Virginia
364,000 Employees
Hybrid Workplace
Year Founded: 1998

What We Do

We’re inspiring and empowering our people to change the world. Powered by the technology of today, you’ll work with diverse teams to build trust and create new client solutions in unexpected ways. The only way we can tackle the challenges of a fast-changing world is with people like you. Be a part of The New Equation.

Why Work With Us

Although we come from different backgrounds and cultures across the firm, our values are what we have in common. They capture our shared aspirations and expectations, and guide how we make decisions and treat others. We care for our people and are committed to inclusion, understanding and respect for all.

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