LLM - Engineer - Senior Associate

PwC; Hyderabad, Chennai District, Bengaluru; Hybride; INR 900 000 - 1 500 000; Plein temps

Résumé du poste

PwC Hyderabad is seeking a data science professional to translate business questions into modeling workstreams, develop exploratory analyses, and apply ML/NLP methods to inform decisions. You will build visualizations and communicate findings to clients and internal teams, using AI tools and programming languages to refine analytic solutions.

Collaborating with client teams, mentoring juniors, and upholding professional standards while adapting to changing requirements will be core

Qualifications

• Degree or coursework in AI/ robotics, analytics, CS, IT, ML, MIS, or related fields.
• Experience applying AI fluency and ML methods to client solutions.
• Ability to interpret data to inform insights and recommendations.
• Strong critical thinking skills to break down complex concepts.
• Ability to build client relationships while anticipating team needs.
• Develop technical skills across data science workflows.
• Maintain professional standards while navigating ambiguity.

Responsabilités

• Analyzing complex data science problems and translating business questions into modeling and analysis workstreams
• Developing exploratory and descriptive analyses to surface patterns, trends, and actionable insights from large datasets
• Applying statistical modeling, machine learning, and natural language processing methods to support data-driven decisions
• Building data visualizations and clear summaries that communicate findings to clients and internal teams
• Using AI tools, programming languages, and digital tooling to develop, test, and refine analytic solutions
• Reviewing data quality, feature design, and model outputs to validate accuracy and consistency
• Collaborating with client teams to understand business context, clarify priorities, and shape analytic approaches
• Mentoring junior team members by reviewing work products, sharing methods, and guiding task execution
• Interpreting feedback and changing requirements to refine analyses, deliverables, and technical approaches
• Maintaining professional and technical standards while supporting client service engagements and broader project objectives

Connaissances

AI fluency

Machine Learning

Data interpretation

Critical thinking

Client relationships

Data science workflows

Professional standards

Ambiguity navigation

Formation

Artificial Intelligence and Robotics

Business Analytics

Computer Science

Data Science

Statistics

Description du poste

Role & responsibilities

• Analyzing complex data science problems and translating business questions into modeling and analysis workstreams
• Developing exploratory and descriptive analyses to surface patterns, trends, and actionable insights from large datasets
• Applying statistical modeling, machine learning, and natural language processing methods to support data-driven decisions
• Building data visualizations and clear summaries that communicate findings to clients and internal teams
• Using AI tools, programming languages, and digital tooling to develop, test, and refine analytic solutions
• Reviewing data quality, feature design, and model outputs to validate accuracy and consistency
• Collaborating with client teams to understand business context, clarify priorities, and shape analytic approaches
• Mentoring junior team members by reviewing work products, sharing methods, and guiding task execution
• Interpreting feedback and changing requirements to refine analyses, deliverables, and technical approaches
• Maintaining professional and technical standards while supporting client service engagements and broader project objectives

What Sets You Apart

• Preference for at least one of the following fields of study: Artificial Intelligence and Robotics, Business Analytics, Computer and Information Science, Computer Engineering, Computer Programming, Data Processing/Analytics/Science, Engineering, Information Technology, Machine Learning, Management Information Systems, Mathematics, Statistics, Systems Engineering
• Applying AI fluency and machine learning methods to client solutions
• Interpreting data to inform insights and recommendations
• Using critical thinking to break down complex concepts
• Building client relationships while anticipating team needs
• Developing technical skills across data science workflows
• Upholding professional standards while navigating ambiguity