PwC

Sr. Data Scientist

Data Scientist in Dallas, TX , Tampa, FL

Posted 2019-06-17
Description

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, including the following areas:

Understanding of NoSQL (Graph, Document, Columnar) 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, Scala, C++, R, SQL, etc. and applying analytical methods to large and complex datasets leveraging one of those languages;
Applying statistical modelling, algorithms, data mining and machine learning algorithms problem solving;
Managing business development such as client relationship management and leading and contributing to client proposals;
Delivering and tracking successfully large-scale projects, including ownership of architecture solutions and managing change;
Leading, training and working with other data scientists in designing effective analytical approaches taking into consideration performance and scalability to large datasets;
Manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources;
Demonstrating proven ability with NLP and text based extraction techniques;
Developing data science analytic models and simultaneously operationalizing these models so they can run in an automated context; and,
Understanding of machine learning algorithms, such as k-NN, GBM, Neural Networks Naive Bayes, SVM, and Decision Forests. 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:
Understanding of NoSQL (Graph, Document, Columnar) 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, Scala, C++, R, SQL, etc. and applying analytical methods to large and complex datasets leveraging one of those languages;
Applying statistical modelling, algorithms, data mining and machine learning algorithms problem solving;
Managing business development such as client relationship management and leading and contributing to client proposals;
Delivering and tracking successfully large scale projects; including ownership of architecture solutions and managing change;
Leading, training and working with other data scientists in designing effective analytical approaches taking into consideration performance and scalability to large datasets;
Manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources;
Demonstrating proven ability with NLP and text based extraction techniques;
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; and,
Understanding of machine learning algorithms, such as k-NN, GBM, Neural Networks Naive Bayes, SVM, and Decision Forests.
Utilizing and applying knowledge commonly used data science packages including Spark, Pandas, SciPy, and Numpy;
Demonstrating familiarity with thorough learning architectures used for text analysis, computer vision and signal processing;
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 knowledge of technologies such as H20.ai, Google Machine Learning and Deep learning;
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;
Developing end to end deep learning solutions for structured and unstructured data problems;
Developing and deploying A.I. solutions as part of a larger automation pipeline;
Utilizing programming skills and knowledge on how to write models which can be directly used in production as part of a large scale system;
Using common cloud computing platforms including AWS and GCP in addition to their respective utilities for managing and manipulating large data sources, model, development, and deployment; and,
Visualizing and communicating analytical results, using technologies such as HTML, JavaScript, D3, Tableau, and PowerBI.

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Company summary

PwC is all about you. Your personal and professional development, your achievement, your lifelong learning, your individuality and your choices. Whether you're just starting out or an experienced professional, your future starts here.

Perks

We offer innovative and inspiring ways to reward our people and we are transparent in the way we talk with our people about pay. Our total rewards package is aimed to deliver the value needed to meet staff’s needs beyond just base compensation.

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