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 Associate, 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:
- 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 broad range 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.
Our mandate is to quickly explore new technologies to determine what is relevant for our clients and Firm to invest in. Our work has a tremendous impact on how PwC and our clients do business. Our Data Scientists possess exceptional technical prowess matched by their ability to communicate results to other data scientists, clients, and internal stakeholders.
Job Requirements and Preferences:
Minimum Degree Required:
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:
Preferred Fields of Study:
Computer and Information Science, Mathematics, Computer Engineering, Artificial Intelligence and Robotics, Mathematical Statistics, Statistics, Economics, Operations Management/Research
Additional Educational Preferences:
PhD highly preferred
Demonstrates thorough abilities and/or a proven record of success:
- Exploring new analytical technologies and evaluate their technical and commercial viability;
- Working across entire pipeline: data ingestion, feature engineering, ML model development, visualization of results, and packaging solutions into applications/production ready tools;
- Working across various data mediums: text, audio, imagery, sensory, and structured data;
- Working in (6) 2-week sprint cycles to develop proof-of-concepts and prototype models that can be demoed and explained to data scientists, internal stakeholders, and clients;
- Testing and rejecting hypotheses around data processing and ML model building;
- Experimenting, fail quickly, and recognize when you need assistance vs. concluding a technology is not suitable for the task;
- Building ML pipelines that ingest, clean data, and make predictions;
- Focusing on AI and ML techniques that are broadly applicable across all industries;
- Staying abreast of new AI research from leading labs by reading papers and experimenting with code;
- Developing innovative solutions and perspectives on AI that can be published in academic journals/arXiv and shared with clients;
- Applying ML techniques to address a variety of problems (e.g. consumer segmentation, revenue forecasting, image classification, etc.);
- Understanding ML algorithms (e.g. k-nearest neighbors, random forests, ensemble methods, deep neural networks, etc.) and when it is appropriate to use each technique;
- Understanding open-source deep learning frameworks (PyTorch, Keras, Tensorflow);
- Understanding text pre-processing and normalization techniques, such as tokenization, POS tagging and knowledge of Named Entity Extraction, Document Classification, Topic Modeling, Text summarization and concepts behind application;
- Building ML models and systems, interpreting their output, and communicating the results; and,
- Moving models from development to production; conducting lab research and publishing work.
Demonstrates thorough abilities and/or a proven record of success in the Essential 8: AI, Blockchain, Augmented Reality, Drones, IoT, Robotics, Virtual Reality and 3D printing in addition to:
- Demonstrating knowledge in Data Storage Technologies: SQL, NoSQL, Postgres, Neo4j, Hadoop, cloud-based databases such as GCP BigQuery, and different storage formats (e.g. Parquet, etc.);
- Demonstrating knowledge in Data Processing Tools: Python (Numpy, Pandas, etc.), Spark, cloud-based solutions such as GCP DataFlow;
- Demonstrating knowledge in Machine Learning Libraries: Python (scikit-learn, genism, etc.), TensorFlow, Keras, PyTorch, Spark MLlib, NLTK, spaCy;
- Demonstrating knowledge in NLU/NLP domain: Sentiment Analysis, Chatbots & Virtual Assistants, Text Classification, Text Extraction, Machine Translation, Text Summarization, Intent Classification, Speech Recognition, STT, TTS;
- Demonstrating knowledge in productionization and containerization technologies: GitHub, Flask, Docker, Kubernetes, Azure DevOps, GCP, Azure, AWS.
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.
For positions in Albany (NY), California, Colorado, Nevada, New York City, Washington State, or Westchester County (NY), please visit the following link for pay range information: https://pwc.to/payrange-v1-productstechseniorassociate