Job Description

Line of ServiceInternal Firm Services Industry/SectorNot Applicable SpecialismIFS - Internal Firm Services - Other Management LevelManager & SummaryA career in our Advisory Acceleration Centre is the natural extension of PwC's leading

Line of Service Internal Firm Services Industry/Sector Not Applicable Specialism IFS - Internal Firm Services - Other Management Level Manager & 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. : Product and Technology (P&T) 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, P&T is the team for you. A career in our P&T, will provide you with a unique opportunity to build transformative products and innovative mechanisms that bring new insights to our business and customers that can help identify business gaps, solve problems, and build new business opportunities. Emerging Technologies, within PwC, provides fast, insightful analysis of complex marketing and operational issues, where intelligent use of data holds the key to better decisions and actions. 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. Basic Qualifications: Level: Senior Manager Minimum Year(s) of Experience : 7 - 9 years of overall experience with at least 5 years dedicated advanced analytics and ML Level of Education/ Specific Schools: Graduate/Post Graduate from reputed institute(s) with relevant experience Field of Experience/ Specific Degree: B.Tech./M.Tech/Masters Degree or its equivalent /MBA Preferred Fields of Study : Computer and Information Science, Artificial Intelligence and Robotics, Mathematical Statistics, Statistics, Mathematics, Computer Engineering, Data Processing/Analytics/Science Knowledge Required : Demonstrates intimate abilities and/or a proven record of success in the following areas: Understanding statistical or numerical methods application, data mining or data-driven problem solving Demonstrating thought leader level abilities in the use of statistical modelling, algorithms, data mining and machine learning algorithms Demonstrating proven delivery within a number of large scale projects Demonstrating ownership of architecture solutions and managing change Understanding business development such as client relationship management and leading and contributing to client proposals Communicating project findings orally and visually, to both technical and executive audiences Developing people through effectively supervising, coaching, and mentoring staff 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. Demonstrates intimate abilities and/or a proven record of success in the following areas: Demonstrated ability to continuously learn new technologies and quickly evaluate their technical and commercial viability Demonstrating thought leader-level abilities in commonly used data science packages including Spark, Pandas, SciPy, and Numpy Leveraging familiarity with deep learning architectures used for text analysis, computer vision and signal processing Developing end to end deep learning solutions for structured and unstructured data problems Developing and deploying AI 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 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 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 Experience conducting research in a lab and publishing work is a plus. Experience with following technologies: Programming : Python (must) , having experience in R is a plus Machine Learning Libraries : Python (Numpy, Pandas, scikit-learn, gensim, etc.), TensorFlow, Keras, PyTorch, Spark MLlib, NLTK, spaCy) Visualization : Python (like Matplotlib, Seaborn, bokeh, etc.), third party libraries (like Power BI, Tableau) Productionization and containerization technologies (Good to have) : GitHub, Flask, Docker, Kubernetes, Azure DevOps, GCP, Azure, AWS Role and Responsibilities: Leadership: Leading initiatives aligned with the growth of the team and of the firm Providing strategic thinking, solutions and roadmaps while driving architectural recommendation Interacting and collaborating with other teams to increase synergy and open new avenues of development Supervising and mentoring the resources on projects Managing communication and project delivery among the involved teams Leading the team operations activities Quickly explore new analytical technologies and evaluate their technical and commercial viability Work in sprint cycles to develop proof-of-concepts and prototype models that can be demoed and explained to data scientists, internal stakeholders, and clients Quickly test and reject hypotheses around data processing and machine learning model building Experiment, fail quickly, and recognize when you need assistance vs. when you conclude that a technology is not suitable for the task Build machine learning pipelines that ingest, clean data, and make predictions Develop, deploy and manage production pipeline of ML models automate the deployment pipeline Stay abreast of new AI research from leading labs by reading papers and experimenting with code Develop innovative solutions and perspectives on AI that can be published in academic journals/arXiv and shared with clients 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 Not Specified Available for Work Visa Sponsorship No Government Clearance Required No