Customer 

 The Customer Team empowers organizations to build deeper relationships with customers through innovative strategies, advanced analytics, GenAI, transformative technologies, and creative design. We enable Deloitte client service teams to enhance customer experience and drive sustained growth and customer value creation and capture, through customer and commercial strategies, digital product and innovation, marketing, commerce, sales, and service. We are a team of strategists, data scientists, operators, creatives, designers, engineers, and architects, balancing business strategy, technology, creativity, and ongoing managed services to help solve the biggest problems that impact customers, partners, constituents, and the workforce. We also offer Business Process as a Service, enabling organizations to streamline operations and achieve greater efficiency through scalable, technology-enabled managed insights that guide ongoing transformation and operational excellence. 

Position Summary 

 Level: Manager

 As an AI & Analytics Manager within CS&D, you will lead end-to-end AI/ML/GenAI programs that enhance client pricing, marketing, sales, products, and customer experience strategies. You will combine hands-on technical depth with strategic consulting and people leadership.

Work you’ll do 

 1. Lead AI/ML/GenAI Delivery & Solution Development Across CS&D

• Lead end-to-end AI/ML/GenAI initiatives across pricing optimization, segmentation, marketing effectiveness, personalization, demand forecasting, customer insights, and commercial analytics.
• Translate business objectives into analytical approaches and oversee the full lifecycle - data exploration, experimentation, modeling, validation, deployment, and adoption.
• Guide development of predictive models, clustering algorithms, recommendation systems, marketing/personalization models, optimization engines, and time-series forecasting.
• Lead development of NLP and LLM-based applications including RAG pipelines, prompt engineering, embeddings, fine-tuning, and agent-based systems.
• Ensure solutions meet standards of accuracy, fairness, interpretability, governance, and performance.

2. Client & Stakeholder Leadership

• Liaison with onshore and client executives to understand requirements, shape workstreams, and jointly drive insight-to-action.
• Collaborate with senior leaders to translate complex analytical findings into clear business recommendations aligned to commercial outcomes.
• Support pre-sales, proposals, and client pursuits with solution design and thought leadership.

3. Lead a High-Performing AI, Data Science & Engineering Team

• Lead, mentor, and grow teams of Data Scientists, ML Engineers, Data Engineers, and AI specialists.
• Drive best practices across model development, code quality, documentation, review processes, and deployment.
• Promote a collaborative, inclusive, high-performance culture that encourages innovation and continuous learning.

4. AI Engineering, Data Engineering & MLOps Integration

• Oversee implementation of AI/ML/GenAI solutions using MLOps practices, CI/CD pipelines, automated retraining, monitoring, and governance.
• Partner with Data Engineering teams to build scalable architectures including Lakehouse environments, distributed computing, robust ETL/ELT pipelines, and real-time ingestion workflows using Databricks, PySpark, Kafka, Snowflake, and cloud-native services.
• Ensure seamless integration of analytical solutions into enterprise systems across Azure, AWS, and GCP.

5. Market Intelligence & Advanced Commercial Insights

• Guide pricing analytics, elasticity modeling, margin optimization, and product affinity frameworks.
• Oversee segmentation, customer lifecycle modeling, campaign analytics, and marketing mix insights.
• Leverage market, competitive, and technology trends to inform commercial strategy recommendations.

6. Practice Development & Eminence

• Develop proprietary accelerators, frameworks, and reusable assets for AI/ML/GenAI and commercial analytics.
• Contribute to firm eminence through thought leadership, internal capability-building, and mentoring of junior practitioners.

The team: 

The Customer Strategy & Design (CS&D) team is a core part of Deloitte’s Customer portfolio, helping organizations reimagine customer engagement, drive growth, and enhance experiences across the lifecycle. We operate at the intersection of strategy, design, and digital transformation, bringing together strategists, designers, analysts, and industry experts. 

We work with C-level leaders to tackle complex challenges—from launching new ventures and redefining go-to-market strategies to shaping omnichannel experiences and driving marketing, sales, pricing, and service excellence. Our strength lies in delivering executable strategies that balance long-term vision with practical implementation. 

Partnering across industries, we ensure that our solutions deliver both measurable impact and meaningful customer outcomes, guiding clients from insight to execution. 

Qualifications 

 Must Have Skills/Project Experience/Certifications: 

• 10+ years of experience in AI/ML/Analytics/Data Science with demonstrated delivery of end-to-end AI & GenAI solutions.
• 5+ years of hands-on project leadership delivering AI/ML models into production environments.
• Proven experience managing and mentoring multi-disciplinary teams (typically 5–10 members).
• Strong Python and SQL expertise.
• Experience with deep learning, NLP, LLMs, and GenAI tools/frameworks.
• Working knowledge of cloud platforms and data engineering fundamentals.

Key Areas of Expertise

• AI & GenAI
• NLP, LLMs, embeddings, RAG pipelines, prompt engineering
• Fine-tuning, agent-based architecture, generative AI applications
• Advanced Analytics
• ML algorithms: XGBoost, Random Forest, SVM, Gradient Boosting, clustering, regression, time-series
• Pricing optimization, segmentation, MMM, elasticity, recommendation systems
• Data Engineering & MLOps
• ETL/ELT (PySpark, SQL, Databricks, Airflow, ADF, Snowflake)
• CI/CD, IaC, observability, distributed systems, scalable cloud architectures
• Cloud Platforms
• Azure, AWS, GCP, OpenAI, Nvidia ecosystem
• Visualization & Business Communication
• Tableau, Power BI, executive storytelling, commercial analytics translation

 Good to Have Skills/Project Experience/Certifications:  

• Experience designing commercial analytics solutions in domains such as Retail, Consumer, TMT, Life Sciences, Healthcare, Energy, or Industrial sectors.
• Exposure to global client interaction, particularly US-based teams.

 Education:  

• Master’s degree in data science, AI/ML, Statistics, Engineering, Economics, or MBA with analytics concentration.

Location: 

• Bengaluru / Hyderabad