A career in our Analytics Innovation practice, within Analytics, will provide you with the opportunity to combine consulting and industry expertise with data science capabilities. We use descriptive and predictive analytical techniques to incorporate client, third-party, and proprietary data to help answer questions and design solutions to our clients most pressing business issues.
Our team helps leverage data to rapidly discover, quantify, and deliver value from data with intelligent analytics and scalable end-to-end business solutions. This includes helping our clients drive analytics adoption, accelerating value delivery, developing in house talent, and building solutions and trust in data.
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 an authentic and inclusive leader, at all grades/levels and in all lines of service. 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 Senior Associate, 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:
Use feedback and reflection to develop self awareness, personal strengths and address development areas.
Delegate to others to provide stretch opportunities and coach to help deliver results.
Develop new ideas and propose innovative solutions to problems.
Use a broad range of tools and techniques to extract insights from from current trends in business area.
Review your work and that of others for quality, accuracy and relevance.
Share relevant thought leadership.
Use straightforward communication, in a structured way, when influencing others.
Able to read situations and modify behavior to build quality, diverse relationships.
Uphold the firm's code of ethics and business conduct.
Job Requirements and Preferences:
Minimum Degree Required: Bachelor Degree
Required Fields of Study: Statistics, Economics, Engineering, Operations Management/Research, Computer and Information Science, Computer Engineering, Computer Systems Analysis, Computer Management, Management Information Systems, Mathematics
Additional Educational Requirements: Other quantitative fields of study may be considered
Minimum Years of Experience: 3 year(s)
Degree Preferred: Master Degree
Preferred Fields of Study: Computer and Information Science, Economics, Economics and Finance, Economics and Finance & Technology, Engineering, Operations Management/Research, Statistics, Mathematics
Preferred Knowledge/Skills: Demonstrates thorough knowledge and/or a proven record of success in the following areas: - New technology learning and quickly evaluating their technical and commercial viability; - Machine learning techniques for addressing a variety of problems (e.g. consumer segmentation, revenue forecasting, image classification, etc.); and, - Machine learning algorithms (e.g. k-nearest neighbors, random forests, ensemble methods, deep neural networks, etc.) and when it is appropriate to use each technique.
Demonstrates thorough abilities and/or a proven record of success as a team leader including the following areas: - Building machine learning models and systems, interpreting their output, and communicating the results; - Moving models from development to production; and, - Conducting research in a lab and publishing work.
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.