Line of Service
AdvisoryIndustry/Sector
Not ApplicableSpecialism
Data, Analytics & AIManagement Level
Senior AssociateJob Description & Summary
At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth.Focused on relationships, you are building meaningful client connections, and learning how to manage and inspire others. Navigating increasingly complex situations, you are growing your personal brand, deepening technical expertise and awareness of your strengths. You are expected to anticipate the needs of your teams and clients, and to deliver quality. Embracing increased ambiguity, you are comfortable when the path forward isn’t clear, you ask questions, and you use these moments as opportunities to grow.
Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to:
Responsibilities:
· Lead the design, development, and deployment of production-level machine learning models, with a focus on generative AI models such as Large Language Models (LLMs), Generative Adversarial Networks (GANs), and Variational Autoencoders (VAEs).
· Provide advanced technical support for existing AI models, including bug fixes, addressing complex issues, and facilitating model expansion for new business cases.
· Act as a liaison between data scientists, cloud engineers, data engineers, and the business team to diagnose and resolve issues related to model performance and deployment.
· Lead the continuous improvement of support processes and workflows for ML applications.
· Develop, monitor, and maintain end-to-end machine learning pipelines (MLOps) including data preparation, feature engineering, model training, and deployment.
· Utilize Azure AI Foundry to build, test, and deploy cutting-edge AI-driven solutions and generative AI applications.
· Build model performance benchmarking, evaluation, and monitoring capabilities.
· Assess model performance to understand bugs, inefficiencies, and their root cause.
· Document and communicate best practices and troubleshooting procedures to support teams and stakeholders.
· Coordinate and mentor the Machine Learning Engineering team, promoting best practices and code quality.
· Stay current with the latest advancements in AI and machine learning technologies to provide informed support and recommendations.
Mandatory skill sets:
· Strong experience working with advanced data analysis on large datasets.
· Hands-on experience with Azure for managing the end-to-end ML lifecycle.
· Proven experience with Azure AI Foundry for building and deploying AI-driven solutions.
· Familiarity with Snowflake and its AI/ML offerings.
· Experience in both front-end(UI/UX) and backend (API development, database management) technologies to build end-to-end solutions.
· Proficiency with data science and data engineering tools such as scikit-learn, XGBoost, pandas, NumPy, SciPy, and Jupyter notebooks.
· Strong understanding of software engineering tools and practices (Python, Git, CI/CD principles).
Preferred skill sets:
· Excellent problem-solving skills and attention to detail.
· Must be able to function independently as well as work in a collaborative team environment.
· Willingness to teach and learn new technologies.
Years of experience required:
4 – 7 yrs
Education qualification:
Btech/MBA/MCA
Education (if blank, degree and/or field of study not specified)
Degrees/Field of Study required: Bachelor of Engineering, Master of Business AdministrationDegrees/Field of Study preferred:Certifications (if blank, certifications not specified)
Required Skills
Artificial Intelligence (AI)Optional Skills
Accepting Feedback, Accepting Feedback, Active Listening, AI Implementation, Analytical Thinking, C++ Programming Language, Communication, Complex Data Analysis, Creativity, Data Analysis, Data Infrastructure, Data Integration, Data Modeling, Data Pipeline, Data Quality, Deep Learning, Embracing Change, Emotional Regulation, Empathy, GPU Programming, Inclusion, Intellectual Curiosity, Java (Programming Language), Learning Agility, Machine Learning {+ 25 more}Desired Languages (If blank, desired languages not specified)
Travel Requirements
Not SpecifiedAvailable for Work Visa Sponsorship?
NoGovernment Clearance Required?
NoJob Posting End Date