PwC Applied Scientist: Machine Learning - Sr. Manager (PwC Labs) in Seattle, Washington
PwC Labs is focused on standardizing, automating, delivering tools and processes and exploring emerging technologies that drive efficiency and enable our people to reimagine the possible. Process improvement, transformation, effective use of innovative technology and data & analytics, and leveraging alternative delivery solutions are key areas of focus to drive additional value for our firm.
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.
The Lab’s Data Innovation and Product Team focuses on identifying and prioritizing emerging technologies to develop solutions for commercialization, and to provide solutions that provide insights from new and existing data to develop new business opportunities and improve the firm’s efficiency and effectiveness across all of our technology functions.
Job Requirements and Preferences :
Basic Qualifications :
Minimum Degree Required :
Doctor of Philosophy
Additional Educational Requirements :
In addition to a PhD, Candidate will have at least 7 years of professional experience involving technology-focused process improvements, product development, transformations, and/or system implementations.
Minimum Years of Experience :
Preferred Qualifications :
Preferred Fields of Study :
Computer and Information Science, Physics, Mathematics
Additional Educational Preferences :
PhD in applied or computer sciences, physics, mathematics, cognitive sciences, and other quantitative sciences.
Preferred Knowledge/Skills :
Demonstrates intimate abilities and/or a proven record of success as a team leader in the following
Building personalization solutions, Search, Recommendation and intelligent content mechanisms;
Evaluating new technologies to quickly determine their long-term viability within PwCs enterprise wide technology stack, serving 50k+ professionals, and scale up to large enterprise commercial products;
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 fast-paced product development environment;
Publishing work through AI institutes and journals;
Demonstrating thorough understanding of complex machine learning algorithms, data analysis techniques, and data science tools, to address a variety of challenging business problems in the areas of natural language understanding, computer vision, and unsupervised learning;
Building a variety of machine learning models and more importantly, knowing when and why it is appropriate to use each technique: KNN, Logistic Regression, Naive Bayes, Random Forests, Support Vector Machines, XGBoost, Deep Neural Networks, K-means and Hierarchical Clustering etc.;
Building machine learning models, data pipelines, and autonomous systems and autonomous decision making, interpreting their output, and communicating the results to a non-technical audience;
Building scalable personalization systems for commercial products and services; and,
Demonstrating experience with Ad revenue and marketing systems.
Demonstrates intimate abilities and/or a proven record of success with a subset of the following technologies:
Understanding Data Storage Technologies including SQL, NoSQL, Hadoop, cloud-based databases such as GCP BigQuery, and different storage formats (e.g. Parquet, etc.);
Data Processing Tools including Python (Numpy, Pandas, etc.), Spark, and cloud-based solutions such as GCP DataFlow;
Machine Learning Libraries including Python (scikit-learn, gensim, etc.), TensorFlow, Keras, PyTorch, and Spark MLlib;
NLP and text extraction techniques including document topic analysis, document clustering and classification, named entity extraction/resolution, creating word/sentence embeddings (numerical vector representations), sentiment analysis etc.;
Code management, model productionization and containerization technologies including GitHub, Flask, Docker, and Kubernetes.
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.
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.