ConvergeCONSUMER - Data Science Manager - Innovation_Delivery_Transformation

Are you an experienced Data Scientist who has led the development of world-class software or digital products? Are you looking for an opportunity to expand your scope and lead products used by some of the biggest and most influential businesses around the world? If the answer to these questions is yes, we would like to talk with you.

The Team

ConvergeCONSUMER ™ is a product-driven business that combines differentiated consumer insights with robust prediction and optimization capabilities to help consumer-focused businesses improve decision-making and deliver personalized experiences to drive growth, consumer loyalty, and profitability. We operate with the speed and agility of a startup within the world's largest professional services firm.

We drive value for our clients by optimizing decisions and actions at a level of granularity only made possible with today's data and technology. ConvergeCONSUMER's suite of solutions helps consumer-facing businesses prosper in a world being re-shaped by convergence, where the lines between industries, competitors and collaborators, consumers and suppliers, and even human and artificial intelligence have blurred. Our approach for addressing this complexity is simple: we combine Deloitte's next-generation technology platforms with decades of experience in the consumer sector and a deep understanding of its unique issues and challenges to drive profitability and future growth for our clients.

Recruiting for this role ends on 3/27/2026.

Work you'll do

As a Data Science Manager, you will play a critical role in applying advanced analytics and machine learning to solve complex client business problems. You will work closely with Product Managers, Product Owners, and Project Managers to understand how data products and analytical assets can be effectively implemented to meet client needs. This role requires strong hands-on expertise in exploratory data analysis, forecasting, and model development, as well as the ability to translate analytical insights into clear, market-relevant narratives for technical and non-technical stakeholders. In addition to delivering high-quality analytical solutions, you will help guide teams toward best practices in model development, deployment, and software lifecycle management, while continuously advancing capabilities across AI, ML, cloud, and big data technologies.

Key Responsibilities:

• Lead technical solutioning across client engagements spanning forecasting, pricing, promotion, inventory, and customer intelligence.
• Translate ambiguous executive challenges into structured problem statements, data requirements, and product configurations.
• Own executive relationships with client stakeholders (VP+), including influencing roadmap adoption, accelerating time-to-value, and unlocking expansion opportunities.
• Develop and communicate proof-of-value stories that turn use cases into long-term transformation programs.
• Architect and deploy multi-module ConvergeCONSUMER solutions across multiple functional domains.
• Partner closely with Product, Engineering, and Data Science teams to configure optimization engines, validate model outputs, and ensure system precision.
• Build agentic decision flows that embed ConCON intelligence into existing business processes and workflows.
• Act as a connective tissue across go-to-market, product, delivery, and engineering teams to ensure aligned execution.
• Coach junior team members on technical acumen, client management, and product configuration.
• Contribute to platform feedback loops by translating field experience into prioritized product improvements.

The successful candidate will possess

• Strong track record of technical delivery and client leadership within consulting, enterprise software, or AI platforms.
• Hands-on experience working with one or more of the following: price optimization, demand forecasting, promotion ROI, assortment planning, store clustering, customer segmentation, or identity resolution.
• Ability to operate fluently across business and technical stakeholders - from C-suite to data engineers.
• Hands-on experience building production-grade analytics/ML solutions (notebook-to-production), including code quality, testing, and deployment collaboration with engineering teams.
• Expert Python skills and experience using PySpark for scalable workloads
• Experience navigating messy data and using SQL or other tools to extract and transform it into usable signal for data science activities.
• Hands-on contribution to solution development, including prototyping, feature engineering, and model evaluation to validate impact.
• Expertise in predictive modeling (e.g., tree-based methods, GLMs, neural networks), including model selection, validation, and fit-for-purpose evaluation.
• Familiarity with optimization modeling techniques (e.g., linear programming, constraint-based solvers)
• Experience maintaining data science solutions in production environment, including data and model m