AI/ML & Data Science Leader

Leading AI, ML & data teams that ship at enterprise scale.

For 19+ years I have led AI/ML, data science, and data engineering initiatives, building high-performing teams and delivering enterprise-scale AI, data, and analytics solutions. Currently Senior Manager, Data Science at Lowe’s.

Balaji Nagarajan

About me

I am a data science and engineering leader with 19+ years of experience building AI, ML, and data platforms that operate at enterprise scale. My work spans the full lifecycle, from large-scale data pipelines and lakehouse architectures to model training, MLOps, and production Generative and Agentic AI. Today I lead data science teams at Lowe’s, driving AI/ML strategy, roadmap, and execution across store operations, merchandising, and asset protection. I care deeply about mentoring engineers and scientists and turning ambitious ideas into reliable, decision-ready products.

AI & Machine Learning

Generative AIAgentic AILLMs & RAGMLOpsTensorFlowPyTorchVertex AI

Data Engineering

SparkKafkaAirflowBigQueryDelta LakeApache IcebergDatabricks

Cloud & Platform

GCPAzureKubernetesDockerCloudera

Leadership

Team LeadershipAI/ML StrategyData ArchitectureMentoring
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Years of experience
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Countries with solutions deployed
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Enterprise AI/ML products
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Published book

Areas of expertise

Generative & Agentic AI

Building LLM-powered and agentic applications, including NLP-to-SQL, AI assistants, and LLM-as-a-Judge quality platforms.

AI/ML Engineering & MLOps

Feature engineering, model training, and deployment with TensorFlow, PyTorch, Vertex AI, Kubeflow, and MLflow.

Large-Scale Data Engineering

Real-time streaming and batch pipelines on Spark, Kafka, and Airflow with lakehouse and data-mesh architectures.

Cloud Data Platforms

Distributed processing and cost-optimized platforms across GCP, Azure, Databricks, and BigQuery.

Analytics & Insight

Retail scorecards, forecasting, and fraud detection that turn data into measurable business outcomes.

Team & Strategy Leadership

Leading data science and engineering teams, setting AI/ML roadmap, and mentoring at scale.

Work that shipped

Optimization at Scale

AI-Powered Space Optimization

A machine-learning system that optimizes product placement and shelf-space utilization across a large retail fleet. I engineered a heavily parallelized, distributed compute pipeline to make the optimization tractable at scale, improving space utilization and sales performance. Backed by published research (OPTIMUS).

Read the paper →
Generative AI

Conversational Analytics Assistant

A Generative AI assistant that lets business users query enterprise data warehouses in plain English (NLP-to-SQL), returning summaries and insights that democratize data access for non-technical teams.

AI Quality

GenAI Quality Platform

A unified AI quality platform using an LLM-as-a-Judge approach to automatically surface quality and reliability issues in production Generative AI applications.

ML in Retail

AI-Driven Replenishment

Machine-learning predictions that help retail stores prioritize shelf replenishment, outperforming manual scan-based methods across a complex, large-scale operational workflow.

Real-time Analytics

Real-Time Store Performance Platform

A 360° store-performance platform powered by real-time POS sales streaming, enabling data-driven operational decisions across a large store fleet.

My journey

Experience

Mar 2025 - Present
Senior Manager, Data Science
Lowe’s Inc. · Charlotte, NC
Feb 2018 - Mar 2025
Principal Data Engineer
Lowe’s Inc. · Charlotte, NC
Apr 2010 - Feb 2018
Big Data Solution Architect
Nielsen · Chicago, IL
Aug 2006 - Apr 2010
Sr. Software Engineer
HTC Global Services · Chennai, India

Education

2023 - 2024
M.Tech, Data Science & Engineering
BITS Pilani, India
2008 - 2009
MBA
University of Madras, India
2002 - 2006
B.Tech, Information Technology
Anna University, India

My book

Breaking Into AI cover Breaking Into AI

Breaking Into AI

The Complete Roadmap to Becoming an AI Engineer from Scratch: LLMs, Agents, RAG, and a 90-Day Action Plan for Software and Data Engineers.

A practical, no-fluff roadmap for software and data engineers who want to become AI engineers. It covers LLMs, agents, RAG, and a concrete 90-day action plan drawn from nearly two decades on the front line of every major platform shift.

View on Amazon →

Let's connect

Always glad to exchange ideas on AI, data, and building teams - or to talk through an interesting problem. Find me on LinkedIn.

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