Rapid Prototyping - Data Science - Manager

Pwc Phoenix , AZ 85002

Posted 3 months ago

A career in our Data Science practice, within Innovation services, will provide you with the opportunity to help our clients' tax departments redesign, redefine, and redeploy tax to be a strategic asset across the enterprise. You'll focus on assisting clients incorporate increased automation in the tax reporting process, increase analytic capabilities through data integration, and create solid internal controls that will enable the Tax function to deliver better quality output and contribute more strategically to organisational decision making. Our team focuses on developing cutting edge data analytic and automation applications that provide data and visualisation support for large and small complex data sources.


As a Manager, you'll work as part of a team of problem solvers with extensive consulting and industry experience, helping our clients solve their complex business issues from strategy to execution. Specific responsibilities include but are not limited to:

  • Proactively assist in the management of a portfolio of clients, while reporting to Senior Managers and above

  • Be involved in the financial management of clients

  • Be actively involved in business development activities to help identify and research opportunities on new/existing clients

  • Contribute to the development of your own and team's technical acumen

  • Develop strategies to solve complex technical challenges

  • Assist in the management and delivering of large projects

  • Train, coach, and supervise staff

  • Keep up to date with local and national business and economic issues

  • Continue to develop internal relationships and your PwC brand

Job Requirements and Preferences:

Basic Qualifications:

Minimum Degree Required:

Bachelor Degree

Minimum Years of Experience:
5 year(s) of experience in data analytics, development and programming.

Preferred Qualifications:

Preferred Knowledge/Skills:

Demonstrates extensive knowledge and/or a proven record of success in applied subject matter such as IT, finance, accounting, energy or health care role emphasizing data analytics for a global network of professional services firms, including the following areas:

  • Understanding of NoSQL (Graph, Document, Columar) database models, XML, relational and other database models and associated SQL;
  • Understanding of ETL tools and techniques, such as tools like Talent, Mapforce, how to map transformation and flow of data from a source to a target system;
  • Performing in development language environments e.g. Python, Java or equivalent and applying analytical methods to large and complex datasets leveraging one of those languages;
  • Automating complex processes; and,
  • Proven ability in data analytics management.

Demonstrates extensive abilities and/or a proven record of success in the application of statistical or numerical methods, data mining or data-driven problem solving, including the following areas:

  • Utilizing and applying into projects knowledge of Python based data science tools such as Pandas and Numpy;

  • Utilizing programming skills and knowledge on how to write models which can be directly used in production as part of a large scale system;

  • Utilizing and applying into projects knowledge of data wrangling techniques and scripting languages with proven ability in working on a cloud based infrastructure environment;

  • Understanding of not only how to develop data science analytic models but how to operationalize these models so they can run in an automated context;

  • Understanding of machine learning algorithms, such as k-NN, GBM, Neural Networks Naive Bayes, SVM, and Decision Forests;

  • Utilizing and applying into projects knowledge of technologies such as H20.ai, Google Machine Learning and Deep learning;

  • Proven ability with NLP and text based extraction techniques;

  • Working independently with minimal guidance;

  • Leveraging problem solving and troubleshooting skills with proven ability exercising mature judgment;

  • Prioritizing effectively workload to meet deadlines and work objectives;

  • Writing clearly and succinctly in a manner that appeals to a wide audience;

  • Communicating complex engineering concepts succinctly to senior non-technical and technical decision makers;

  • Performing development, data analytics and programming/scripting, especially Python, Java, Scala, C++, R, SQL, etc.;

  • Applying techniques such as multivariate regressions, Bayesian probabilities, clustering algorithms, machine learning, dynamic programming, stochastic-processes, queuing theory, algorithmic knowledge to efficiently research and solve complex development problems and application of engineering methods to define, predict and evaluate the results obtained;

  • Visualizing and communicating analytical results, ideally using open source visualization technologies such as HTML, JavaScript, and related packages such as D3;

  • Using large data sets, along with analytical scripting tools and visualization platforms to produce actionable insights for clients; data cleansing, transformation, and modeling in order to produce a clear story that is easily comprehended by non-technical audiences;

  • Leading, training and working with other data scientists in designing effective analytical approaches taking into consideration performance and scalability to large datasets; and,

  • Performing unit and system testing to validate the output of the analytic procedures against expected results.

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.

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