US Tech - Data Scientist - Gen AI Solutions

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 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 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:

• Take action to ensure everyone has a voice, inviting opinion from all.
• Establish the root causes of issues and tackle them, rather than just the symptoms.
• Initiate open and honest 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.
• Develop specialised expertise in one or more areas.
• Advise stakeholders on relevant technical issues for their business area.
• Navigate the complexities of global teams and engagements.
• Build trust with teams and stakeholders through open and honest conversation.
• 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:
6 year(s)
Preferred Qualifications:
Degree Preferred:
Master Degree
Preferred Fields of Study:
Computer and Information Science, Mathematics, Computer Engineering, Artificial Intelligence and Robotics, Statistics, Data Processing/Analytics/Science, Mathematical Statistics
Preferred Knowledge/Skills:
Demonstrating intimate abilities and/or a proven record of success as a team leader with the technical knowledge and skills in areas of application development that may include:

• Collaborating with cross-functional teams to understand business requirements and identify opportunities for leveraging data-driven solutions;
• Designing and developing end-to-end generative AI solutions, from data collection and preprocessing to model training and deployment;
• Applying advanced statistical analysis and machine learning techniques to extract insights and patterns from complex datasets;
• Developing and implementing algorithms and models to solve business problems, (e.g. natural language processing, computer vision, and recommendation systems);
• Conducting exploratory data analysis to identify trends, outliers, and potential data quality issues;
• Collaborating with software engineering teams to incorporate data science solutions into reusable software components;
• Staying current with the latest advancements in data science and machine learning;
• Identifying opportunities to apply new techniques and technologies;
• Mentoring and providing guidance to junior data scientists and fostering a culture of continuous learning and growth;
• Demonstrating experience as a data scientist, with a focus on developing generative AI solutions;
• Leading, training, and working with other data scientists to design analytical approaches;
• Considering performance and scalability of large datasets;
• Understanding of NoSQL (Graph, Document, Columnar) database models, XML, relational and other database models, and associated SQL;
• 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, Snaplogic Talend, Mapforce, etc.;
• Utilizing experience with NLP and text-based extraction techniques;
• 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; and,
• 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 both verbally and in written formats with project team members;
• Presenting findings to both technical and non-technical stakeholders; and,
• Working in an agile environment and delivering proven results within deadlines.

Learn more about how we work: https://pwc.to/how-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.
Applications will be accepted until the position is filled or the posting is removed, unless otherwise set forth on the following webpage. Please visit this link for information about anticipated application deadlines: https://pwc.to/us-application-deadlines
For positions in California, Colorado, Hawaii, Nevada, New York State, or Washington State, or for opportunities that will report to a supervisor, office or other work site in New York State, please visit the following link for pay range information: https://pwc.to/payrange-v1-productstechseniormanager
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