PwC Digital Upskilling-Data Scientist-Director

A career in Products and Technology would provide you the opportunity to be part of an organization that is building a leading tech experience that solves big challenges for our firm and our clients. Our products and tech-driven solutions are how we move faster, cut through complexity and fuel growth. We start with the problem and solve it with experience and tech know-how. Our skilled technologists, data scientists, product managers and business strategists are passionate about using technology to accelerate change. Our external facing team focuses on the process of collecting, cleansing, transforming, designing and modeling data for the purposes of drawing critical insights and conclusions that support decision making. This team designs and develops data science, machine learning, natural language processing and related solutions to address business needs. They assist in the management and delivery of large data science projects, work with a wide range of automation teams to validate findings and proposed analytics solutions for our clients.

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 Director, 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:

• Support team to disrupt, improve and evolve ways of working when necessary.
• Arrange and sponsor appropriate assignments and experiences to help people realise their potential and support their long-term aspirations.
• Identify gaps in the market and spot opportunities to create value propositions.
• Look for opportunities to scale efficiencies and new ways of working across multiple projects and environments.
• Create an environment where people and technology thrive together to accomplish more than they could apart.
• I promote and encourage others to value difference when working in diverse teams.
• Drive and take ownership for developing connections that help deliver what is best for our people and stakeholders.
• Influence and facilitate the creation of long-term relationships which add value to the firm.
• Uphold the firm’s code of ethics and business conduct.

Job Requirements and Preferences:

Basic Qualifications:

Minimum Degree Required:
Master Degree

Minimum Years of Experience:
10 year(s)

Preferred Qualifications:

Degree Preferred:
Doctor of Philosophy

Preferred Fields of Study:
Artificial Intelligence and Robotics, Computer Engineering, Computer Programming, Mathematical Statistics, Mathematics

Preferred Knowledge/Skills:

Demonstrates thought leader-level abilities with, and/or a proven record of success directing efforts in the following areas:

• Understanding statistical or numerical methods application, data mining or data-driven problem solving;
• Demonstrating thought leader level abilities in the use of statistical modelling, algorithms, data mining and machine learning algorithms;
• Understanding business development such as client relationship management and leading and contributing to client proposals;
• Demonstrating proven delivery within a number of large scale projects;
• Demonstrating ownership of architecture solutions and managing change;
• Communicating project findings orally and visually, to both technical and executive audiences;
• Developing people through effectively supervising, coaching, and mentoring staff;
• Leading, training, and working with other data scientists in designing effective analytical approaches taking into consideration performance and scalability to large datasets; and,
• Manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources.

Demonstrates thought leader-level abilities with, and/or a proven record of success directing efforts in the following areas:

• Demonstrating thought leader-level abilities in commonly used data science packages including Spark, Pandas, SciPy, and Numpy;
• Leveraging familiarity with deep learning architectures used for text analysis, computer vision and signal processing;
• Developing end to end deep learning solutions for structured and unstructured data problems;
• Developing and deploying A.I. solutions as part of a larger automation pipeline;
• Utilizing programming skills and knowledge on how to write models which can be directly used in production as part of a large scale system;
• Understanding of not only how to develop data science analytic models but how to operationalize these models so they can run in an automated context;
• Using Data visualization software such as tableau and qlikview in addition to web visualization libraries;
• Demonstrating proven ability with NLP and text based extraction techniques; and,
• Using common cloud computing platforms including AWS and GCP in addition to their respective utilities for managing and manipulating large data sources, model, development, and deployment.