Job Location: Bangalore
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.
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.
Data Scientist/ML Engineer – Senior Associate
- Design and develop data science, machine learning, natural language processing, deep
learning and related solutions to address business needs.
- Design and implement current state-of-art machine learning, algorithms related to
Forecasting, Classification, Data/Text Mining, NLP, Computer Vision, Decision Trees,
Adaptive Decision Algorithms, Random Forest, Search Algorithms, Neural Networks,
Deep Learning Algorithms.
- Converting the AI models into microservices and deploy them using dockers.
- Deploy AI models in production using docker with automated data pipelines.
- 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 at least 8 years of total experience and at least 6 years of relevant experience in
the field of AI/ML.
- Bachelor’s or Master’s Degree in Computer Science, Engineering or other technical
discipline (BE, BTech, MCA).
- Experience in analyzing complex problems and translating them to data science
algorithms with due attention to computational efficiency and testing at scale.
- Experience in machine learning, supervised and unsupervised: Forecasting,
Classification, Data/Text Mining, NLP, Computer Vision, Decision Trees, Adaptive
Decision Algorithms, Random Forest, Search Algorithms, Neural Networks, Deep
Learning Algorithms.
- Worked with at least one mainstream machine learning frameworks, including Caffe,
ConvNet, Tensor Flow, Keras, Torch.
- Working proficiency with SQL and relational databases, data warehouse.
- Experience with big data platforms – Hadoop (Hive, Pig, Map Reduce, HQL) / Spark /
H20.
- Experience with Google Cloud Platform, AWS or Azure.
- Experience with GPU/CUDA for computational efficiency.
- Strong implementation experience with languages, such as Python, Java, or Scala and
familiarity with Linux/Unix/Shell environments.
- Strong hands-on skills in sourcing, cleaning, identifying patterns and outliers,
manipulating and analyzing large volumes of big data using distributed computing
platform.
- Understanding of NoSQL (Graph, Document, Columnar) database models, XML,
relational and other database models and associated SQL.
- 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 several 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, Computer Vision and text-based extraction techniques.
- Understanding of not only how to develop data science analytic models but how to
operationalize and deploy the models as microservices in production using Dockers and
automated pipelines.
or numerical methods, data mining, data wrangling and 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.
- 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 Azure, 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, Tableau, and Power BI.
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
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