Products & Tech - Senior Associate in Data Science

Line of Service: Internal Firm Services Industry/Sector: Not Applicable Specialism: IFS - Internal Firm Services - Other Management Level: Senior Associate Job Description & Summary: A career in Products and Technology provides an opportunity to bring PwC's strategy to life by integrating products and technology into all services we provide. Our clients expect us to assemble the right team with the best technology to solve their pressing issues. Products and Technology helps PwC tackle these challenges and fuel the advancement of our enterprise. Our team comprises skilled technologists, data scientists, product managers, and business strategists who utilize technology to bring about transformation. Our squad designs, develops, and codes the methodologies, procedures, and systems used to gather all forms of data and create models that provide predictions to applications, automated process flows, and stakeholders. A Data Scientist obtains domain context from stakeholders, constructs hypotheses and prediction tasks, identifies, and forms supporting data sources, conducts tests with various algorithms to craft prediction tasks, carries out validation and model tests to improve performance, generates pipelines that can automate training and predictions with unseen or production data, identifies important insights from data, and contextualizes model outputs for communication with stakeholders (product owners, process managers, and end users). To truly stand out and prepare us for the future in an ever-changing world, everyone at PwC needs to be a purpose-driven and values-oriented leader at every level. To assist us in achieving this, we have the PwC Professional, our global leadership development framework. It offers a single set of expectations across our sectors, regions, and career journeys, and provides transparency on the skills we require as individuals to succeed and progress in our careers, present and future. As a Senior Associate, you'll collaborate within a team of problem solvers, contributing to solving 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 wide variety 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. Preferred Knowledge/Skills: +2 years of experience demonstrating thorough abilities and a proven record of success as a team leader in several areas: - Evaluating new technologies to quickly determine their long-term viability within PwC's enterprise-wide technology stack, serving 50k+ professionals. - Understanding a business problem and being able to translate the problem into a hypothesis that can be tested using various data science techniques. - Conducting research in a lab environment and publishing work through AI institutes and journals. - Demonstrating a thorough understanding of complex machine learning algorithms, data analysis techniques, and data science tools, to tackle diverse challenging business problems in the fields of natural language understanding, computer vision, and unsupervised learning. - Building a range of machine learning models and importantly, understanding when and why it's suitable to use each technique: KNN, Logistic Regression, Naive Bayes, Random Forests, Support Vector Machines, XGBoost, Deep Neural Networks, K-means and Hierarchical Clustering, prompt and engineering tuning for LLMs, fine-tuning and domain training LLMs, etc. - Building machine learning models, data pipelines, and autonomous systems, interpreting their output, and communicating the results to a non-technical audience. - Performing DevOps/engineering tasks in publishing and deploying AI assets in live production environments suitable for large scale adoption for 55k+ professionals throughout the US. Education: (If blank, degree and/or field of study not specified) Degrees/Field of Study required: Degrees/Field of Study preferred: Certifications: (If blank, certifications not specified) Required Skills: Natural Language Processing (NLP), Natural Language Programming (NLP) Optional Skills: Desired Languages: (If blank, desired languages not specified) Travel Requirements: Up to 20% Available for Work Visa Sponsorship? No Government Clearance Required? No Job Posting End Date: