IN_Senior Manager_AI/ML_Data and Analytics_Advisory_Pune

Line of Service

Advisory

Industry/Sector

Not Applicable

Specialism

Data, Analytics & AI

Management Level

Senior Manager

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.

In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and implementing data pipelines, data integration, and data transformation solutions.

*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:

We are seeking to recruit an SM/ Director with AI proficiency who can help build practice and drive sales in the GCC segment.

Responsibilities:

AI & Analytics Transformation Leadership (40%)

Lead large, complex, multi-workstream AI and data transformation programmes for marquee clients — enterprise data modernisation, GenAI/Agentic AI deployment, MLOps industrialisation, and analytics operating-model redesign

Act as the senior technical authority: review solution architectures, model design choices, evaluation frameworks, and Responsible AI controls — not just delegate them

Drive AI adoption and change management: use-case portfolio definition, value cases, AI Centre of Excellence stand-up, and workforce enablement

Establish measurable outcomes — cycle-time reduction, cost-to-serve, decision quality, and ROI — and hold delivery accountable to them

Business Development & Sales (30%)

Own an annual sales/origination target; build and convert a qualified pipeline across new GCC accounts

Lead pursuits end-to-end: qualification, win strategy, solutioning, commercials, orals, and negotiation

Build CXO-level relationships (CDO, CIO, CTO, CAIO, Head of Digital) and grow accounts from project to programme to platform

Practice & Capability Building (20%)

Build reusable IP, accelerators, and industry AI solutions; contribute to PwC's GenAI/Agentic AI asset library

Scale the team: hiring, capability roadmaps, technical mentoring, and career sponsorship for Managers and Senior Managers

Champion Responsible AI — governance, model risk, bias/fairness testing, explainability, and alignment to the EU AI Act, India's DPDP Act, and RBI/SEBI/IRDAI expectations

Thought Leadership & Market Presence (10%)

Author points of view, whitepapers and industry reports; represent PwC at NASSCOM, industry forums, and client roundtables

Shape the market narrative on enterprise AI in India

Mandatory skill sets:

Technology Consulting Experience

Minimum 7+ years in a client-facing technology/management consulting role, owning delivery and commercial outcomes. Must have operated in a billable, engagement-led model.

Hands-on AI Leader

Demonstrable hands-on depth — has personally built, deployed and scaled ML/GenAI solutions (not purely advisory/PMO). Must be able to whiteboard a RAG architecture, critique an evaluation framework, and debate model trade-offs credibly. Must have led at least 2–3 enterprise AI transformations from strategy through production..

Firm Pedigree

Current or recent experience at a Big 4 (Deloitte, EY, KPMG), Accenture Technology, CG or a Tier-1 GCC/Global tech consulting arm at Senior Manager / Associate Director / Director level.

Sales Background

Proven origination track record — must be able to evidence personally sold/influenced revenue (indicatively ₹10–20 Cr+ cumulative or a consistent annual target). Comfortable owning a number.

Technical Depth Expected

Must have working, current fluency in:

GenAI & Agentic AI — LLM selection & fine-tuning, RAG architectures, agent orchestration (LangChain/LangGraph, Semantic Kernel, AutoGen), prompt & context engineering, evaluation/guardrails

Classical ML & Data Science — supervised/unsupervised learning, forecasting, NLP, computer vision, causal inference, optimisation

Modern Data Stack — Databricks, Snowflake, Azure Fabric/Synapse, AWS (SageMaker/Bedrock), GCP (Vertex AI), dbt, Kafka, lakehouse & data mesh architectures

MLOps/LLMOps — CI/CD for models, feature stores, monitoring, drift detection, model registries, cost & latency optimisation

Governance — data governance, master data, Responsible AI frameworks, model risk management

Behavioral & Leadership Competencies

Executive presence — credible and persuasive with boards and CXOs; able to translate technical complexity into business language

Commercial instinct — spots and shapes opportunity in every client conversation

Player-coach — willing to go deep into a problem, and equally capable of scaling through others

Resilience & ambiguity tolerance — thrives in undefined, fast-moving transformation contexts

Ethical rigour — uncompromising on quality, independence and Responsible AI

Preferred skill sets:

Sector depth in BFSI, Consumer/Retail, Pharma/Life Sciences, or Manufacturing

Experience serving Global Capability Centres (GCCs) in India

Cloud/platform certifications — Azure AI Engineer, AWS ML Specialty, Databricks Data Engineer/ML Professional, GCP Professional ML Engineer

Published research, patents, or open-source contributions in AI/ML

Experience with AI-enabled managed services or outcome-based commercial models

Years of experience required:

10–15 years total post-qualification experience, with a clear trajectory to Director.

Education qualification:

B.E./B.Tech from IIT / NIT / BITS / Tier-1 engineering institute, and/or MBA from IIM / ISB / XLRI / FMS / MDI / top global school. Advanced degree (M.S./Ph.D.) in CS, Statistics, Data Science or Applied Mathematics is a strong plus.

Education (if blank, degree and/or field of study not specified)

Degrees/Field of Study required: Master of Business Administration, Bachelor of Engineering

Degrees/Field of Study preferred:

Certifications (if blank, certifications not specified)

Required Skills

Data Engineering

Optional Skills

Accepting Feedback, Accepting Feedback, Active Listening, Agile Scalability, AI Fluency, AI-Human Collaboration, Amazon Web Services (AWS), Analytical Thinking, Apache Airflow, Apache Hadoop, Azure Data Factory, Coaching and Feedback, Communication, Creativity, Data Anonymization, Data Architecture, Database Administration, Database Management System (DBMS), Database Optimization, Database Security Best Practices, Databricks Unified Data Analytics Platform, Data Engineering, Data Engineering Platforms, Data Infrastructure, Data Integration {+ 38 more}

Desired Languages (If blank, desired languages not specified)

Travel Requirements

Not Sp