Lead Data Scientist

CommerceIQ is an AI-powered digital commerce platform that helps brands optimize their online sales, retail media ROI, and market share across over 900 retailers in 50+ countries. The company works with top CPG brands like Coca-Cola and Nestle, having raised over $200M. This Lead Data Scientist role involves leveraging advanced machine learning, deep learning, and NLP expertise to develop and deploy scalable AI solutions, leading a team of scientists and engineers, and translating cutting-edge research into practical business impact.

Must Have

• Strong background in ML, deep learning, and NLP.
• Experience training and fine-tuning large-scale models (LLMs, transformers).
• Expertise with Parameter-Efficient Fine-Tuning (PEFT) approaches.
• Proficiency in PyTorch, TensorFlow, Hugging Face ecosystem.
• Success adapting foundation models to domain-specific applications.
• Ability to design, evaluate, and improve models with robust validation.
• Experience in applied AI problems (NLP, computer vision, multimodal).
• Proven ability to lead and mentor applied scientists and ML engineers.
• Master’s or Ph.D. in Computer Science or related field.
• 5+ years hands-on experience in applied ML and data science.

Good to Have

• Experience with distributed training frameworks (DeepSpeed, PyTorch Lightning).
• Basic understanding of MLOps best practices.
• Experience with large datasets, feature engineering, and data pipelines.
• Knowledge of GPU/TPU optimization and scaling ML workloads.
• Strong cross-functional collaboration skills.
• Ability to translate cutting-edge research into scalable solutions.
• Excellent communication and presentation skills.
• Continuous learner aware of generative AI trends.

Company Overview

CommerceIQ’s AI-powered digital commerce platform is revolutionizing the way brands sell online. Our unified ecommerce management solutions empower brands to make smarter, faster decisions through insights that optimize the digital shelf, increase retail media ROI and fuel incremental sales across the world’s largest marketplaces. With a global network of more than 900 retailers, our end-to-end platform helps 2,200+ of the world’s leading brands streamline marketing, supply chain, and sales operations to profitably grow market share in more than 50 countries. 10 out of the top 12 CPG brands work with us, including Coca-Cola, Nestle, Colgate-Palmolive, and Mondelez. We’ve raised over $200M from some of the top investors including SoftBank, Insight Partners, and Madrona. Learn more at commerceiq.ai_

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Technical Expertise

• Strong background in machine learning, deep learning, and NLP, with proven experience in training and fine-tuning large-scale models (LLMs, transformers, diffusion models, etc.).
• Hands-on expertise with Parameter-Efficient Fine-Tuning (PEFT) approaches such as LoRA, prefix tuning, adapters, and quantization-aware training.
• Proficiency in PyTorch, TensorFlow, Hugging Face ecosystem and good to have distributed training frameworks (e.g., DeepSpeed, PyTorch Lightning, Ray).
• Basic understanding of MLOps best practices, including experiment tracking, model versioning, CI/CD for ML pipelines, and deployment in production environments.
• Experience working with large datasets, feature engineering, and data pipelines, leveraging tools such as Spark, Databricks, or cloud-native ML services (AWS Sagemaker, GCP Vertex AI or Azure ML).
• Knowledge of GPU/TPU optimization, mixed precision training, and scaling ML workloads on cloud or HPC environments.
• Applied Problem-Solving

Mandatory skill -

• Demonstrated success in adapting foundation models to domain-specific applications through fine-tuning or transfer learning.

Mandatory skill -

• Strong ability to design, evaluate, and improve models using robust validation strategies, bias/fairness checks, and performance optimization techniques.
• Experience in working on applied AI problems across NLP, computer vision, or multimodal systems or any other domain.

Leadership & Collaboration

• Proven ability to lead and mentor a team of applied scientists and ML engineers, providing technical guidance and fostering innovation.
• Strong cross-functional collaboration skills to work with product, engineering, and business stakeholders to deliver impactful AI solutions.
• Ability to translate cutting-edge research into practical, scalable solutions that meet real-world business needs.

Other

• Excellent communication and presentation skills to articulate complex ML concepts to both technical and non-technical audiences.
• Continuous learner with awareness of emerging trends in generative AI, foundation models, and efficient ML techniques.

Education & Experience

• Master’s or Ph.D. in Computer Science, Machine Learning, Data Science, Statistics, or a related field.
• 5+ years of hands-on experience in applied machine learning and data science.

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability status or any other category prohibited by applicable law.