Anti-Financial Crimes, Data Scientist, Sr. Assoc. (Financial Services)

Key Skills

Microsoft-Excel, Java Programming, Python Programming, C++, SQL, PowerBI, Tableau, R Programming, Spotfire, Powerpoint

Job Description

A career in our Analytics Technology practice 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. You'll 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 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, coaching them to deliver results.
• Demonstrate critical thinking and the ability to bring order to unstructured problems.
• Use a broad range of tools and techniques to extract insights from current industry or sector trends.
• Review your work and that of others for quality, accuracy and relevance.
• Know how and when to use tools available for a given situation and can explain the reasons for this choice.
• Seek and embrace opportunities which give exposure to different situations, environments and perspectives.
• Use straightforward communication, in a structured way, when influencing and connecting with others.
• Able to read situations and modify behavior to build quality relationships.
• 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:

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:

3 year(s) of relevant experience.

Preferred Qualifications:

Preferred Knowledge/Skills:

Demonstrates thorough 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 such as multivariate regressions, Bayesian probabilities, clustering algorithms, machine learning, dynamic programming, stochastic-processes, queuing theory, algorithmic knowledge 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, PowerBI and Qlikview.

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

• Assisting with the delivery and tracking of large-scale projects;
• Demonstrating aptitude for building and implementing 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;
• Supporting engagement leads in the interpretation and presentation of model results and model choice rationale;
• 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
• Managing and/or contributing to project planning, engagement administration, budget management, and successful completion of engagement work stream(s).