Line of Service
Internal Firm ServicesIndustry/Sector
Not ApplicableSpecialism
Data ScienceManagement Level
ManagerJob Description & Summary
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.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 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:
Job Title: Data Scientist
Minimum Degree Required:
Bachelor's 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.
Preferred Qualifications:
Degree Preferred:
Master's degree
Additional Educational Preferences:
Computer and Information Science, Mathematics, Computer Engineering, Artificial Intelligence and Robotics, Statistics, Data Processing/Analytics/Science, Mathematical Statistics
Job Summary:
Collaborating with cross-functional teams to understand business requirements and identify opportunities for identifying opportunities using data and then leveraging AI data-driven solutions.
Applying advanced statistical analysis, regression analysis and machine learning techniques to extract insights and patterns from complex datasets.
Conducting exploratory data analysis to identify trends, outliers, and potential data quality issues.
Developing and implementing algorithms and models to solve business problems, such as; natural language processing, computer vision, and recommendation systems.
Collaborating with various engineering teams to integrate data science and automation solutions into reusable software components.
Designing and developing end-to-end generative AI solutions, from data collection and preprocessing to model training and deployment.
Staying current with the latest advancements in data science and machine learning and proactively identifying opportunities to apply new techniques and technologies.
Understand Data Engineering and Data Optimization to increase performance and scalability of large datasets.
Understanding of NoSQL (Graph, Document, Columnar) database models, XML, relational and other database models, and associated SQL. Vector Database is a plus.
Working knowledge of programming skills in Python, R, or similar languages, with experience in data manipulation, analysis, and modeling libraries e.g., (NumPy, Pandas, scikit-learn, TensorFlow, PyTorch).
Understanding of machine learning algorithms e.g., (k-NN, GBM, Neural Networks Naive Bayes, SVM, and Decision Forests), statistical analysis, and data visualization techniques.
Working experience with deep learning frameworks and architectures e.g., (CNNs, RNNs, GANs).
Utilizing experience working with large-scale datasets and distributed computing frameworks e.g., (Hadoop, Spark) is a plus.
Understanding of ETL tools and techniques, like Azure Data Factory, Alteryx, etc.
Understanding of all Microsoft Office Applications like the Dataverse, Power Apps, Power Automation, and Azure Data Factory
Understanding of how to develop and operationalize data science analytical models so these models can run in an automated context.
Understanding of how to map transformation and flow of data from a source to a target system.
Problem-solving skills and the ability to translate business requirements into data-driven solutions.
Demonstrating intimate abilities and/or a proven record of success in managing stakeholders (e.g., executive level leadership) relationships related to various projects.
Communicating effectively both verbally and in written formats with project team members; and Presenting findings to both technical and non-technical stakeholders.
Working in an agile environment and delivering proven results within deadlines.
Education (if blank, degree and/or field of study not specified)
Degrees/Field of Study required:Degrees/Field of Study preferred: Master DegreeCertifications (if blank, certifications not specified)
Required Skills
Automation Technology, Azure Data Factory, Data Analytics, ETL Tools, Generative AIOptional Skills
Desired Languages (If blank, desired languages not specified)
Travel Requirements
0%Available for Work Visa Sponsorship?
NoGovernment Clearance Required?
NoJob Posting End Date