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Senior Manager - Machine Learning

Senior Manager - Machine Learning

ClearDemandSurat, IN
3 days ago
Job description

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 :

  • MS / PhD from reputed institution with a delivery focus.
  • 5+ years of experience in data science, with a proven track record of delivering impactful data-driven solutions.
  • Delivered AI / ML products / features to production.
  • Seen the complete cycle from Scoping & analysis, Data Ops, Modelling, MLOps, Post deployment analysis.
  • Experts in Supervised and Semi-Supervised learning techniques. Hands-on in ML Frameworks - Pytorch or TensorFlow.
  • Hands-on in Deep learning models. Developed and fine-tuned Transformer based models. ( Input output metric, Sampling technique)
  • Deep understanding of Transformers, GNN models and its related math & internals.
  • Exhibit high coding standards and create production quality code with maximum efficiency.
  • Hands-on in Data analysis & Data engineering skills involving Sqls, PySpark etc.
  • Exposure to ML & Data services on the cloud – AWS, Azure, GCP Understanding internals of computer hardware - CPU, GPU, TPU is a plus.
  • Can leverage the power of hardware accel to optimize the model execution — PyTorch Glow, cuDNN, is a plus
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