Products & Solutions - Data Science Lead - Sr Manager

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

A career in Products and Technology is an opportunity to bring PwC's strategy to life by driving products and technology into everything we deliver. Our clients expect us to bring the right people and the right technology to solve their biggest problems; Products and Technology is here to help PwC meet that challenge and accelerate the growth of our business. We have skilled technologists, data scientists, product managers and business strategists who are using technology to accelerate change. Our team designs, develops and programs the methods, processes, and systems that are used to collect all forms of data and develop models that serve predictions to applications, automated process flows, and stakeholders. A Data Scientist collects domain context from stakeholders, defines hypothesis and prediction tasks, identifies and creates supporting data sources, conducts experiments with various algorithms to model prediction tasks, undertakes validation and tests of models to improve performance, produces pipelines that can be used to automate training and predictions with unseen or production data, identifies meaningful insights from data sources, and contextualizes model outputs to communicate with stakeholders (product owners, process managers, and end consumers).

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 Manager, 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:

• Encourage everyone to have a voice and invite opinion from all, including quieter members of the team.
• Deal effectively with ambiguous and unstructured problems and situations.
• Initiate open and candid coaching conversations at all levels.
• Move easily between big picture thinking and managing relevant detail.
• Anticipate stakeholder needs, and develop and discuss potential solutions, even before the stakeholder realises they are required.
• Contribute technical knowledge in area of specialism.
• Contribute to an environment where people and technology thrive together to accomplish more than they could apart.
• Navigate the complexities of cross-border and/or diverse teams and engagements.
• Initiate and lead open conversations with teams, clients and stakeholders to build trust.
• Uphold the firm's code of ethics and business conduct.

Job Requirements and Preferences:

Basic Qualifications:

Minimum Degree Required:

Bachelor Degree

Additional Educational Requirements:

Bachelor's degree or in lieu of a degree, demonstrating, in addition to the minimum years of experience required for the role, three years of specialized training and/or progressively responsible work experience in technology for each missing year of college.

Minimum Years of Experience:

10 year(s)

Preferred Qualifications:

Degree Preferred:

Master Degree

Additional Educational Preferences:

Artificial Intelligence and Robotics, Computer Engineering, Computer Programming, Mathematical Statistics, Mathematics

Preferred Knowledge/Skills:

Demonstrates intimate-level abilities and/or a proven record of success managing efforts with identifying and addressing client needs:

• Understanding statistical or numerical methods application, data mining or data-driven problem solving; 
• Demonstrating intimate 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 development 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 intimate-level abilities and/or a proven record of success managing efforts with identifying and addressing client needs:
• Understanding statistical or numerical methods application, data mining or data-driven problem solving; 
• Demonstrating intimate 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 development 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. 
• Demonstrating intimate 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 intimate abilities 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.