Job description

Data Scientist - Senior Associate

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Job Category:   Management Consulting
Line of Service:   Advisory
Location(s):   IL-Chicago|NY-New York
Travel Requirements:   0-20%
Level:   Senior Associate
Job ID:   104763BR
PwC/LOS Overview
PwC is a network of firms committed to delivering quality in assurance, tax and advisory services.

We help resolve complex issues for our clients and identify opportunities. Learn more about us at www.pwc.com/us.

At PwC, we develop leaders at all levels. The distinctive leadership framework we call the PwC Professional (http://pwc.to/pwcpro) provides our people with a road map to grow their skills and build their careers. Our approach to ongoing development shapes employees into leaders, no matter the role or job title.

Are you ready to build a career in a rapidly changing world? Developing as a PwC Professional means that you will be ready
- to create and capture opportunities to advance your career and fulfill your potential. To learn more, visit us at www.pwc.com/careers.

PwC Advisory helps our clients with their most challenging imperatives from strategy through execution. We combine the breadth of knowledge of over 48,000 global professionals with deep industry knowledge to deliver custom solutions for our clients. We work with the world's largest and most complex companies and understand the unique business issues and opportunities our clients face.

Job Description
Our Operations consultants help clients realize competitive advantage from operations. This high performing team translates business strategy into effective operations to drive both growth and profitability. Specific areas of focus include product innovation and development, supply chain, procurement and sourcing, manufacturing operations, service operations, and capital asset programs and operations.

Data Scientists at PwC are expected to be multi-lingual in the sense that their technical prowess must be matched by their ability to communicate results to other data scientists, clients, and internal stakeholders. Our team is capability centric, focusing on AI and machine learning techniques that are broadly applicable across all industries. We work with the gamut of data mediums including text, audio, imagery, sensory, and structured data. Our work involves the use of supervised and unsupervised machine learning algorithms, traditional statistical models, deep neural networks, terabyte scale data, and simulation modelling. We are often tasked with working across the entire pipeline: data ingestion, feature engineering, machine learning model development, visualization of results, and packaging solutions into applications/production ready tools. Our mandate is to quickly explore new technologies to determine what is relevant for our clients and Firm to invest in. Our work is having a tremendous impact on how PwC and our clients do business, whether we are streamlining workflows with machine learning models or helping clients make the right strategic investments in AI.

Position/Program Requirements
Minimum Year(s) of Experience: 3


Minimum Degree Required: Bachelor's degree Engineering, Economics, Statistics, Math, Computer Science, Informatics, Operations Research, or other quantitative disciplines.


Degree Preferred: Master's degree or Doctorate Engineering, Economics, Statistics, Math, Computer Science, Informatics, Operations Research, or other quantitative disciplines.


Knowledge Preferred:

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

- New technology learning and quickly evaluating their technical and commercial viability;

- Machine learning techniques for addressing a variety of problems (e.g. consumer segmentation, revenue forecasting, image classification, etc.); and,

- Machine learning algorithms (e.g. k-nearest neighbors, random forests, ensemble methods, deep neural networks, etc.) and when it is appropriate to use each technique.


Skills Preferred:

Demonstrates thorough abilities and/or a proven record of success as a team leader including the following areas:

- Building machine learning models and systems, interpreting their output, and communicating the results;

- Moving models from development to production; and,

- Conducting research in a lab and publishing work.

Demonstrates thorough abilities and/or a proven record of success with a subset of the following technologies:

- Programming: Python, R, Java, JavaScript, C++, Unix Hardware: sensors, robotics, GPU enabled machine learning, FPGAs, Raspberry Pis, etc.;

- Data Storage Technologies: SQL, NoSQL, Hadoop, cloud-based databases such as GCP BigQuery, and different storage formats (e.g. Parquet, etc.);

- Data Processing Tools: Python (Numpy, Pandas, etc.), Spark, cloud-based solutions such as GCP DataFlow;

- Machine Learning Libraries: Python (scikit-learn, genism, etc.), TensorFlow, Keras, PyTorch, Spark MLlib;

- Visualization: Python (Matplotlib, Seaborn, bokeh, etc.), JavaScript (d3); and,

- Productionization and containerization technologies: GitHub, Flask, Docker, Kubernetes.




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