PwC Financial Crimes, Data Scientist - Exp Assoc (Financial Services) in New York, New York
Specialty/Competency: Data and Analytics Technologies
Industry/Sector: Banking and Capital Markets
Time Type: Full time
Travel Requirements: Up to 80%
A career within Data and Analytics services will provide you with the opportunity to help organisations uncover enterprise insights and drive business results using smarter data analytics. We focus on a collection of organisational technology capabilities, including business intelligence, data management, and data assurance that help our clients drive innovation, growth, and change within their organisations in order to keep up with the changing nature of customers and technology. We make impactful decisions by mixing mind and machine to leverage data, understand and navigate risk, and help our clients gain a competitive edge.
Our team helps clients navigate various analytics applications to get the most value out of their technology investment and foster confidence in their business intelligence. As part of our team, you'll help our clients implement enterprise content and data management applications that improve operational effectiveness and provide impactful data analytics and insights.
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 an 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:
Invite and give in the moment feedback in a constructive manner.
Share and collaborate effectively with others.
Identify and make suggestions for improvements when problems and/or opportunities arise.
Handle, manipulate and analyse data and information responsibly.
Follow risk management and compliance procedures.
Keep up-to-date with developments in area of specialism.
Communicate confidently in a clear, concise and articulate manner - verbally and in the materials I produce.
Build and maintain an internal and external network.
Seek opportunities to learn about how PwC works as a global network of firms.
Uphold the firm's code of ethics and business conduct.
Job Requirements and Preferences :
Basic Qualifications :
Minimum Degree Required :
Required Fields of Study :
Computer and Information Science, Computer and Information Science & Accounting, Economics, Economics and Finance, Economics and Finance & Technology, Engineering, Operations Management/Research, Statistics, Mathematics, Data Processing/Analytics/Science
Additional Educational Requirements :
Other quantitative fields of study may be considered.
Minimum Years of Experience :
1 year(s) of relevant experience.
Preferred Qualifications :
Preferred Knowledge/Skills :
Demonstrates some abilities and/or a proven record of success in the application of statistical methods, data mining or data-driven problem solving, emphasizing a combination of some of the following areas:
Performing in development language environments: e.g. Python, Java, C++, R, SQL, etc. and applying analytical methods to large and complex datasets leveraging one of those languages;
Applying statistical modelling, algorithms, data mining and machine learning algorithms problem solving;
Manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources;
Demonstrating familiarity with machine learning architectures used for text analysis and anomaly detection;
Building modularised, configurable and re-usable statistical and predictive models including (but not limited to) natural language processing, decision trees, multi-label classification, regression analysis and neural networks;
Applying techniques across one or more machine learning model including: multivariate regressions, Bayesian probabilities, clustering algorithms, machine learning, dynamic programming, stochastic-processes, queuing theory, algorithmic knowledge;
Applying machine learning techniques to efficiently research and solve complex development problems and application of engineering methods to define, predict and evaluate the results obtained; and
Visualizing and communicating analytical results, using technologies such as Tableau, Spotfire, Power BI and Qlikview.
Demonstrates some abilities and/or a proven record of success in a combination of some of the following areas:
Assisting with the delivery and tracking of large-scale projects;
Demonstrating aptitude for contributing to the implementation of predictive models in a highly documented, well presented fashion;
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;
Collaborating with business development teams responsible for writing and presenting proposals to prospective clients, leveraging PC applications including Microsoft Word, Excel, PowerPoint, and Project; and
Supporting engagement leads in the interpretation and presentation of model results and model choice rationale.
At PwC, our work model includes three ways of working: virtual, in-person, and flex (a hybrid of in-person and virtual). Visit the following link to learn more: https://pwc.to/ways-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 based in San Francisco, consideration of qualified candidates with arrest and conviction records will be in a manner consistent with the San Francisco Fair Chance Ordinance.
For positions in Colorado, visit the following link for information related to Colorado's Equal Pay for Equal Work Act: https://pwc.to/coloradoadvisoryassociate.