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 experiences 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: Consultant or equivalent
As a Data Science Consultant/Senior Consultant within CS&D, you will deliver data-driven insights, actionable recommendations, and cutting-edge analytical solutions. You’ll play a pivotal role in supporting clients’ commercial strategies with a blend of technical depth and strategic thinking.
Work you’ll do
- Data Science & Analytics Strategy
- Design and implement business-aligned data strategies for pricing, sales, marketing, and product development.
- Integrate data science methods into cross-functional workflows with varied teams.
- Develop predictive models, machine learning algorithms, and advanced statistical techniques (e.g., XGBoost, Random Forest, SVM, clustering, Lasso/Ridge regression).
- Recommend best practices in data governance, quality, and integration.
- Build frameworks for customer segmentation and clustering to enable targeted marketing/product strategies.
- Advanced Data Analysis & Market Intelligence
- Analyze pricing and transaction-level data to identify optimization opportunities.
- Construct financial models to evaluate the impact of pricing on revenue and profitability.
- Track market trends, new technologies, and competitors to support client strategies.
- Execute campaign analytics, market-mix modeling, and customer engagement analyses (e.g., conjoint, product affinity).
- Domain-Specific Solutions
- Healthcare/Life Sciences: Predictive analytics for outcomes, trial optimization.
- Sales/Marketing: Machine learning for dynamic pricing and campaign optimization.
- Product Innovation: Real-time, data-driven insights for product design.
- Consumer/Retail: Forecasting, inventory optimization, loyalty analytics.
- Technology: Predictive modelling, QA automation with AI.
- Advanced Analytics & Model Development
- Build/optimize ML models (classification, regression, clustering, recommendation).
- Apply NLP and deep learning to unstructured data (TensorFlow, PyTorch).
- Recalibrate models for continued business relevance.
- AI Engineering & Emerging Tech
- Design AI solutions using agentic platforms, LLMs, orchestration pipelines.
- Productionize ML models and data pipelines (Spark, Hadoop, MLflow, MLOps).
- Deploy scalable solutions on AWS, Azure, GCP, with modern frameworks.
- Lead LLM-driven, generative AI, and intelligent agent implementations.
- Stakeholder Engagement
- Align analytics strategies with C-suite through workshops/presentations.
- Communicate technical findings in business terms, build client capabilities.
- Support global clients, including real-time consultation during night shifts.
- Infrastructure & Technology Assessment
- Assess data/analytics maturity and recommend platforms and architecture.
- Lead deployment and integration of new analytics tools.
- Practice Development
- Drive business development, proposals, solutioning.
- Author thought leadership, mentor staff, advance firm knowledge sharing.
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:
- 2 - 3 years for consultants. The ideal candidate will bring hands-on experience in applying data science to drive customer-centric growth strategies, with a focus on pricing, segmentation, marketing effectiveness, and advanced analytics. This role sits within the Customer Strategy and Design team and plays a critical part in delivering impactful outcomes across global engagements.
- Professional experience: Experience in strategy consulting from consulting firms, Big 4 firms, OR experience within pricing department in industry with a focus on pricing strategy, planning and technology.
- Industry experience: across below listed industries is preferable Retail, Consumer Goods & Industrial Products ,Telecom, Media & Technology, Life Sciences & Healthcare, Energy & Industrial , Transportation, Hospitality. Good understanding of how businesses price the products and services to different customers in a B2B or B2C or B2B2C environment.
- Core Consulting skills: Managing the pace and delivery of projects including coordination with key project stakeholders, reporting key findings, and contributing to the wider business unit through business development, knowledge sharing and other activities.
- Analytical skills: A strong technical foundation in building analytical solutions and experience with complex data sets, performing quantitative analysis (descriptive and prescriptive) and research (primary and secondary); synthesizing and presenting insights and recommendations from data.
- Key Analytical Focus Areas:
- Customer segmentation and clustering using demographic, behavioural, and transactional data
- Marketing Mix Modeling (MMM) and campaign analytics to assess marketing effectiveness and ROI assessment
- Price and profit optimization models across products and segments
- Conjoint analysis and product affinity modeling for innovation and customer preference alignment
- Demand forecasting, dynamic pricing, and elasticity modeling
- Expertise in Advanced ML & Statistical Methodologies:
- Experience with techniques such as Random Forest, XGBoost, SVM, Gradient Boosting, Time Series Forecasting, Logistic Regression, K-Means Clustering, Hierarchical Clustering, Lasso/Ridge Regression, PCA, Survival Models, and Ensemble Methods
- Familiarity with deep learning models for NLP, image analysis, and unstructured data processing
- AI Engineering & Emerging Platforms:
- Exposure to AI engineering principles for scalable model deployment using CI/CD and MLOps pipelines
- Hands-on experience or understanding of agentic platforms, LLM-based orchestration, or intelligent agent frameworks for task automation and knowledge management
- Working knowledge of integrating ML solutions into production environments and performance optimization
- Mandatory Tools Experience:
- Microsoft Office: Proficient in Microsoft Excel for advanced data analysis and financial modeling, and Microsoft PowerPoint for creating impactful presentations and visualizing data insights
- Python/R: Proficiency in Python or R for data manipulation, statistical analysis, and machine learning
- SQL: Strong command over SQL for data querying and management
- Tableau/Power BI: Experience in data visualization using Tableau or Power BI to communicate insights effectively
Good to Have Skills/Project Experience/Certifications:
- Apache Spark/Hadoop: Familiarity with big data frameworks like Spark or Hadoop for handling large datasets
- TensorFlow/PyTorch: Experience with deep learning frameworks such as TensorFlow or PyTorch for advanced analytical models
- AWS/Azure/GCP: Knowledge of cloud services (AWS, Azure, or GCP) for deploying scalable data science solutions
- SAS: Experience with SAS for advanced analytics, particularly in sectors like healthcare or finance
Education:
- Masters in Statistics, Data Science, etc.
- MBA from Tier 1 B School or Abroad / Masters in Economics with specialization in Data Science
Location:
Bengaluru/Hyderabad