Job Description

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.

Focused on relationships, you are building meaningful client connections, and learning how to manage and inspire others. Navigating increasingly complex situations, you are growing your personal brand, deepening technical expertise and awareness of your strengths. You are expected to anticipate the needs of your teams and clients, and to deliver quality. Embracing increased ambiguity, you are comfortable when the path forward isn’t clear, you ask questions, and you use these moments as opportunities to grow.

Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to:

• Respond effectively to the diverse perspectives, needs, and feelings of others.
• Use a broad range of tools, methodologies and techniques to generate new ideas and solve problems.
• Use critical thinking to break down complex concepts.
• Understand the broader objectives of your project or role and how your work fits into the overall strategy.
• Develop a deeper understanding of the business context and how it is changing.
• Use reflection to develop self awareness, enhance strengths and address development areas.
• Interpret data to inform insights and recommendations.
• Uphold and reinforce professional and technical standards (e.g. refer to specific PwC tax and audit guidance), the Firm's code of conduct, and independence requirements.

As a Senior 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 :
3 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 thorough 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;

• Applying techniques across one or more machine learning models including: multivariate regressions, Bayesian probabilities, clustering algorithms, machine learning, dynamic programming, stochastic-processes, queuing theory, algorithmic knowledge;

• Utilizing intelligent robotic process automation tools (Automation Anywhere, Pega, UiPath, etc. );

• Demonstrating aptitude for conducting quantitative and qualitative analyses of large and complex data as it relates to the project requirements in the financial crimes space; and,

• Visualizing and communicating analytical results, using technologies such as Tableau, Spotfire, Power BI and QlikView. 

Demonstrates thorough abilities and/or a proven record of success in a combination of some of the following areas: 

• Leading a key work stream in an engagement(s), staying educated on current trends and assisting in the development of knowledge capital for team members;

• Working with business development teams responsible for writing and presenting proposals to prospective clients, leveraging PC applications including Microsoft Word, Excel, PowerPoint, and MS Project;

• Supporting practice management for a specific operation or process in a consultative environment;

• Participating in client discussions and meetings actively;

• Communicating a broad range of Firm services;

• Managing engagements including preparing concise, accurate documents and balancing project economics management with the occurrence of unanticipated issues; and,

• Managing and/or contributing to project planning, engagement administration, budget management, and successful completion of engagement work stream(s). 

Learn more about 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:

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: $85,000 - $117,000, 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:

Job Tags

Holiday work, Full time, H1b,

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