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PwC Data Scientist/Machine Learning Engineer - Sr. Associate in Kansas City, Missouri

Specialty/Competency: Deals

Industry/Sector: Not Applicable

Time Type: Full time

Travel Requirements: Up to 20%

A career in Technology and Data Solutions practice, within Deals Transaction Services, provides the opportunity to help organizations realize the potential of mergers, acquisitions, divestitures and capital markets. You will have the opportunity to leverage technology and data to drive better Deal decisions and execute transactions more effectively, helping companies originate, create, execute, and realize value from deals.

Our team consists of well-rounded creative professionals who have a passion and aptitude for building technology driven solutions and pushing the boundaries of innovation in Deals. We are industry leaders in embedding technology, leveraging data analysis, machine learning, and artificial intelligence for a broad range of Deal-focused solutions.

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.

Job Requirements and Preferences :

Basic Qualifications :

Minimum Degree Required :

Bachelor Degree

Required Fields of Study :

Data Processing/Analytics/Science, Computer and Information Science, Computer Engineering, Computer Applications, Software App, Information Technology

Additional Educational Requirements :

Other relevant fields of study may be considered.

Minimum Years of Experience :

3 year(s)

Preferred Qualifications :

Degree Preferred :

Master Degree

Additional Educational Preferences :

Master Degree or Ph.D. in Computer Science, or a related quantitative field.

Certification(s) Preferred :

Certifications with cloud architectures and service offerings of major cloud providers (e.g. Azure, AWS, GCP)

Preferred Knowledge/Skills :

Demonstrates thorough abilities and/or a proven record of success in translating business questions into data problems, and building models and machine learning pipelines to solve those data problems.

Demonstrates through abilities and/or a proven record of success in working out a solution independently when given an analytical business use case, building a Proof-of-Concept (PoC), documenting solutions and code, and communicating results to both technical and non-technical audiences, with an understanding of the assumptions and limitations of algon eithms being applied.

Demonstrates thorough abilities and/or a proven record of success in building end-to-end machine learning systems and pipelines, and can read, understand, and change legacy machine learning and NLP code.

Demonstrates thorough abilities and/or a proven record of success in the following areas:

  • Possesses considerable ability with Python programming;

  • Possesses considerable knowledge about data science concepts and principles;

  • Possesses considerable ability with common machine learning libraries including scikit-learn, pandas, numpy, scipy, Spacy, NLTK, and PyTorch;

  • Possesses considerable ability with a wide range of supervised and unsupervised machine learning algorithms, including regression, classification, clustering, anomaly detection, time series analysis, forecasting, dimensionality reduction, etc.;

  • Possesses considerable level of ability with Predictive modeling;

  • Possesses considerable level of ability with modern Natural Language Processing concepts and algorithms, including embeddings, transfer learning, transformers, and deep learning models for NLP;

  • Possesses thorough level of knowledge about mathematical, statistical, and probabilistic frameworks underlying machine learning algorithms;

  • Possesses considerable level of ability with building and fine-tuning machine learning solutions and leveraging specific machine learning architectures (e.g. deep neural networks, RNNs, CNNs, BERT, etc);

  • Possesses considerable level of ability to learn, understand and work with new emerging technologies, methodologies, and solutions in the Cloud/IT technology space;

  • Possesses thorough level of knowledge about abstract business problems, and executing technical and non-technical endeavors to solve them;

  • Possesses considerable level of ability to communicate with both technologists and business partners;

  • Possesses considerable level of ability to work as a solutions architect, technical product manager, software engineer or frontend/backend web developer for data products or web applications;

  • Possesses considerable level of ability to be a “utility player” and take on various roles, as needed, throughout the solution development lifecycle;

  • Possesses considerable ability to recognize opportunities to solve problems by developing applications or automations, and of identifying abstractions to turn applications into platforms;

  • Possesses considerable ability to think critically and bring order to unstructured problems;

  • Possesses considerable ability to identify and resolve blocking issues, exercise judgment in the face of ambiguity, and ask probing questions to understand problems;

  • Possesses considerable ability to develop a backlog of work and communicate with software engineers;

  • Possesses considerable ability to be hands-on with technical details of architecture and design where required; and,

  • Possesses a thorough level of knowledge about the inner workings of a web application, exposure to systems administration or DevOps operations, automated testing and CI/CD pipelines.

At PwC, our work model includes three ways of working: virtual, in-person, and flex (a hybrid of in-person and virtual). Visit the following link to learn more:

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:

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 Colorado, visit the following link for information related to Colorado's Equal Pay for Equal Work Act: