Senior Manager - Machine Learning

About Clear Demand : Clear Demand is the leader in AI-driven price and promotion optimization for retailers . Our platform transforms pricing from a challenge to a competitive advantage, helping retailers make smarter, data-backed decisions across the entire pricing lifecycle. By integrating competitive intelligence, pricing rules, and demand modelling , we enable retailers to maximize profit, drive growth, and enhance customer loyalty — all while maintaining pricing compliance and brand integrity. With Clear Demand, retailers stay ahead of the market, automate complex pricing decisions, and unlock new opportunities for growth.

Key Responsibilities :

• People management - Lead a team of software engineers, DS, DE, MLE, in the design, development, and delivery of software solutions.
• Program management - Strong program leader that has run program management functions to efficiently deliver ML projects to production and manage its operations.
• Work with Business stakeholders & customers in the Retail Business domain to execute the product vision using the power of AI / ML.
• Scope out the business requirements by performing necessary data-driven statistical analysis.
• Set goals and, objectives using proper business metrics and constraints.
• Conduct exploratory analysis on large volumes of data, understand the statistical shape, and use the right visuals to drive & present the analysis.
• Analyse and extract relevant information from large amounts of data and derive useful insights on a big-data scale.
• Create labelling manuals and work with labellers to manage ground truth data and perform feature engineering as needed.
• Work with software engineering teams, data engineers and ML operations team (Data Labellers, Auditors) to deliver production systems with your deep learning models.
• Select the right model, train, validate, test, optimise neural net models and keep improving our image and text processing models.
• Architecturally optimize the deep learning models for efficient inference, reduce latency, improve throughput, reduce memory footprint without sacrificing model accuracy.
• Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation.
• Create and enhance model monitoring system that could measure data distribution shifts, alert when model performance degrades in production.
• Streamline ML operations by envisioning human in the loop kind of workflows, collect necessary labels / audit information from these workflows / processes, that can feed into improved training and algorithm development process.
• Maintain multiple versions of the model and ensure the controlled release of models.
• Manage and mentor junior data scientists, providing guidance on best practices in data science methodologies and project execution.
• Lead cross-functional teams in the delivery of data-driven projects, ensuring alignment with business goals and timelines.
• Collaborate with stakeholders to define project objectives, deliverables, and timelines.

Qualifications & Experience :