PwC

Data Scientist - Senior Associate - PwC Labs - Ban...

Job description

Line of Service

Advisory

Industry/Sector

Not Applicable

Specialism

Advisory - Other

Management Level

Senior Associate

Job Description & Summary

A career in our Advisory Acceleration Centre is the natural extension of PwC’s leading class global delivery capabilities. We provide premium, cost effective, high quality services that support process quality and delivery capability in support for client engagements.

PwC Labs

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. If as a

professional you are looking to put your skills to work in a product-based, fast paced, entrepreneurial, and

inclusive environment, PwC Labs is the team for you.

A career in our PwC Labs, will provide you with a unique opportunity to build transformative products and

innovate mechanisms that bring new insights to our business and customers that can help identify

business gaps, solve problems, and build new business opportunities.

Day-to-Day Responsibilities

  • Design and develop data science, machine learning, natural language processing, deep learning and related solutions to address business needs

  • Work creatively and analytically to apply cutting edge techniques to specific challenges

  • Assist in the management and delivery of large data science projects

  • Work with a wide range of automation teams to validate findings and proposed analytics solutions

  • Continuously expand personal skill sets and stay up to speed on the latest A.I. trends, tools, methodologies, and techniques


Skills and Experience:

Demonstrates extensive knowledge and/or a proven record of success in data analytics, including the following areas:

  • Ideally 6 to 9 years of relevant experience

  • Bachelor’s Degree in Computer Science, Engineering or other technical discipline (BE, BTech, MCA).

  • Performing in development language environments- e.g. Python, Java, Scala, R, SQL, etc. and applying analytical methods to large and complex datasets leveraging one of those languages

  • Experience in machine learning, natural language processing, deep learning

  • 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 Talend, Map force, how to

map transformation and flow of data from a source to a target system

  • Demonstrates extensive abilities and/or a proven record of success in the application of statistical modelling, algorithms, data mining and machine learning algorithms problem solving

  • A track record of delivery within a number of large-scale projects, demonstrating 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

  • Experience manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources

  • 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

  • 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:

  • Utilizing and applying knowledge commonly used data science packages including Spark, Pandas, SciPy, and Numpy.

  • Familiarity with deep 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

  • 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.

  • Visualizing and communicating analytical results, using technologies such as HTML, JavaScript, D3, Tableau, and PowerBI.

Education (if blank, degree and/or field of study not specified)

Degrees/Field of Study required:

Degrees/Field of Study preferred:

Certifications (if blank, certifications not specified)

Required Skills

Optional Skills

Desired Languages (If blank, desired languages not specified)

Travel Requirements

Available for Work Visa Sponsorship?

Government Clearance Required?

Job Posting End Date

October 15, 2021

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