IN_Senior Associate_ AI/ML/Data Science_Data and Analytics_Advisory_Bangalo at pwc

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

30 Jul, 26

Salary

0.0

Posted On

01 May, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, PyTorch, TensorFlow, GenAI, Azure ML, AWS SageMaker, GCP Vertex AI, Vector databases, RAG pipelines, Prompt engineering, Autonomous agents, Machine learning, Data exploration, Feature engineering, MLOps, Containerization

Industry

Professional Services

Description

Line of Service Advisory Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Associate Job 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. Those in artificial intelligence and machine learning at PwC will focus on developing and implementing advanced AI and ML solutions to drive innovation and enhance business processes. Your work will involve designing and optimising algorithms, models, and systems to enable intelligent decision-making and automation. Why PWC At PwC, you will be part of a vibrant community of solvers that leads with trust and creates distinctive outcomes for our clients and communities. This purpose-led and values-driven work, powered by technology in an environment that drives innovation, will enable you to make a tangible impact in the real world. We reward your contributions, support your wellbeing, and offer inclusive benefits, flexibility programmes and mentorship that will help you thrive in work and life. Together, we grow, learn, care, collaborate, and create a future of infinite experiences for each other. Learn more about us. At PwC, we believe in providing equal employment opportunities, without any discrimination on the grounds of gender, ethnic background, age, disability, marital status, sexual orientation, pregnancy, gender identity or expression, religion or other beliefs, perceived differences and status protected by law. We strive to create an environment where each one of our people can bring their true selves and contribute to their personal growth and the firm’s growth. To enable this, we have zero tolerance for any discrimination and harassment based on the above considerations. Job Description & Summary: A career within Data and Analytics services will provide you with the opportunity to help organisations uncover enterprise insights and drive business results using smarter data analytics. We focus on a collection of organisational technology capabilities, including business intelligence, data management, and data assurance that help our clients drive innovation, growth, and change within their organisations in order to keep up with the changing nature of customers and technology. We make impactful decisions by mixing mind and machine to leverage data, understand and navigate risk, and help our clients gain a competitive edge. Responsibilities: Build and deploy machine learning models for classification, regression, NLP, and computer vision use cases Conduct data exploration, feature engineering, model training, tuning, and performance evaluation Collaborate with data engineers to develop robust data pipelines and integrate models into production systems Work closely with client and deliver projects in the AI/ML space Contribute to reusable assets, accelerators, and internal capability building Develop and deploy AI solutions on cloud platforms (Azure/ AWS/GCP) using MLOps and containerization Mandatory skill sets: 3+ years of experience in AI/ML engineering, with experience in working in a cloud environment Proficiency in Python, PyTorch/TensorFlow, and GenAI/Agentic frameworks Hands-on experience with cloud-native AI services (Azure ML, AWS SageMaker, GCP Vertex AI) Familiarity with vector databases (e.g., FAISS, Pinecone), RAG pipelines, and prompt engineering Strong understanding of autonomous agents, orchestration, and multi-agent systems Excellent communication and stakeholder management skills across geographies Preferred skill sets: Certifications in cloud platforms and AI/ML technologies Exposure to enterprise-grade AI use cases in BFSI, healthcare, retail, or manufacturing Knowledge of Responsible AI, data governance, and compliance frameworks Exposure to Agentic AI, Gen AI Years of experience required: 3 to 8 years Education qualification: BE, B.Tech, ME, M,Tech, MBA, MCA (60% above) Education (if blank, degree and/or field of study not specified) Degrees/Field of Study required: Bachelor of Technology, MBA (Master of Business Administration) Degrees/Field of Study preferred: Certifications (if blank, certifications not specified) Required Skills Artificial Intelligence (AI), Machine Learning 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 Available for Work Visa Sponsorship? Government Clearance Required? Job Posting End Date May 15, 2026 Are you ready to make a difference? Want to unlock new value by applying your unique perspective and talents? You can grow exponentially at PwC. Here, you can uncover hidden talents, build lifelong relationships rooted in trust and empathy and turn challenges into opportunities for innovation. We’ll help you grow your skills through challenging, meaningful work so you can go further.

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Responsibilities

Build and deploy machine learning models for classification, regression, NLP, and computer vision use cases. Collaborate with data engineers to develop robust data pipelines and integrate models into production systems.