🌐 In the heart of today's digital revolution, businesses frequently find themselves navigating through oceans of data. The challenge of extracting valuable insights and driving actionable strategies is formidable. As a seasoned full stack Data Scientist and a leader in MLOps, ML Engineering, ETL pipelines, and DevOps, I guide businesses through these challenges🎯 Data often cloaks its real value behind overwhelming complexity, rendering crucial insights elusive. My unique blend of deep technical expertise and strategic leadership has been the compass guiding businesses through these data labyrinths, converting tangled data threads into lucid, impactful insights🔑 Businesses face persistent hurdles in data management, model deployment, and scalability - stumbling blocks that can stall your growth trajectory. Armed with a track record of enhancing data quality, fine-tuning ETL operations, and architecting robust machine learning infrastructures, I strive to transform these hurdles into steppingstones propelling your business to new heights🚀 Harnessing the immense power of MLOps, robust POCs, and predictive models can be a challenging endeavor. My journey across renowned institutions and past ventures demonstrates how to skillfully exploit marketing analytics, optimize customer engagement, and maximize campaign ROI, thereby driving growth🔧 A vibrant, inclusive, and collaborative work culture is the bedrock of high-performing teams - yet it's a challenge many organizations grapple with. My leadership ethos, deeply rooted in Agile methodologies, fosters a synergy that encourages collaboration, motivating teams to reach their zenith and exceed expectations💫 Beyond the professional sphere, I engage in relentless exploration, venturing into nature's grandeur. As a firm believer in lifelong learning, I commit myself to continually enhancing my skills to stay at the cutting edge of the rapidly evolving data science landscape✅ With a broad expertise spanning AWS services, ETL operations, MLOps frameworks, GitOps, DevOps practices, marketing analytics, Machine Learning, Deep Learning, Python, R, and beyond, I am your veritable toolkit to tackle data challenges and foster business growth📧 If your business is seeking the way out of the data labyrinth, striving to overcome bottlenecks in data operations, or hunting for innovative growth drivers - Let's connect. I am eager to bring my skillset to your table, steering your business towards unparalleled success. Let's embark together on a transformative, data-driven journey | DM at anurag778@gmail.com
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Machine Learning EngineerGraingerChicago, Il, Us
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Data Scientist - Mlops & Cloud InfrastructurePeritushub Feb 2023 - PresentChicago, Illinois, United StatesAt 2ndSight.ai (Client), a pioneering SaaS platform harnessing the power of Conversational AI, I've led the orchestration and deployment of Machine Learning (ML) models through a robust MLOps process, implementing AWS EKS, Kubernetes, and Infrastructure as Code (IaC) with Terraform, within a GitOps framework and utilizing ArgoCD for CI/CD.Key Achievements:• Developed and implemented an efficient MLOps strategy using AWS EKS for Kubernetes cluster management, leading to enhanced monitoring capabilities, optimization, and scalability of ML models.• Leveraged Terraform for Infrastructure as Code (IaC) to automate and manage infrastructure, increasing the agility and speed of ML deployments on AWS EKS and Kubernetes clusters.• Employed a GitOps framework for version control, harnessing the power of Git, and ensuring code consistency and reproducibility across development, staging, and production environments.• Implemented CI/CD pipelines with ArgoCD, enhancing automation, deployment speed, and reliability of ML model releases on AWS EKS and Kubernetes.• Facilitated data collection, preprocessing, and exploratory data analyses using AWS’s extensive suite of analytic tools, further optimizing Kubernetes to handle these workloads.• Orchestrated the creation, deployment, and monitoring of ETL jobs on AWS Glue, integrating them seamlessly with EKS and Kubernetes for efficient ML model training and inference.• Introduced rigorous data quality checks, validation, and cleaning techniques using AWS Data Pipeline and Terraform, maintaining high-quality data for ML model training.• Conducted comprehensive performance evaluations of ML models, using AWS services such as A/B testing and AWS CloudWatch for metrics analysis, identifying improvements, and fine-tuning models for optimal performance on EKS Kubernetes clusters. -
Data Scientist - Deep Learning Model Serving Systems (Delos)Northwestern University Apr 2022 - Jun 2022Evanston, Illinois, United StatesThe Center for Deep Learning (CDL) at Northwestern University developed an MLOps platform that automates everything from data extraction to model deployment.The Deep Learning Model Serving (DELOS) systems at CDL, backed by industry stalwarts such as Motorola, State Farm, and Nvidia, leverage Kubeflow, which in turn relies on Kubernetes. Kubernetes is an open-source container orchestration system, streamlining the automation of deployment, scaling, and management of workloads and services. The project focuses on the creation of a comprehensive infrastructure, deployable as a standalone Helm package, which promotes easy adoption and utilization.Key Achievements:•Engineered a scalable MongoDB Sharded Cluster using Helm Charts on Kubernetes, leading to a 20% increase in large-scale data processing and analysis capabilities while ensuring robust data storage.•Implemented Grafana and TensorBoard for comprehensive ML experiment tracking, mitigating model drift. Utilized advanced visualization tools for data-driven decision-making.•Developed robust drift detection and automatic retraining pipeline in MLOps, ensuring reliable predictions. Pinpointed and addressed performance degradation.•Collaborated on varied challenges, driving scalability with Proof of Concepts for successful project implementations. Fostered innovation and achieved exceptional results.•Implemented GitOps-based CI/CD pipelines (GitLab, GitHub Actions, Argo CD) for accelerated software delivery. Streamlined workflows for code reliability and enhanced productivity.•Leveraged Docker for scalable deployment of ML models across diverse environments. Simplified deployment processes.•Developed REST API endpoints to serve TensorFlow models, enabling real-time predictions and seamless integration. Empowered decision-making and process optimization.•Demonstrated reliable solutions in collaborative environments. Adapted to achieve successful outcomes. Strong individual performance and teamwork. -
Founder, Head Of Technology – Applied Ai / MlBluebell Fabcare Jul 2016 - Aug 2021Indore, Madhya Pradesh, IndiaA premier omnichannel retail powerhouse, delivering diverse, high-quality fashion merchandise and exceptional digital shopping experiences.Key Achievements:• Spearheaded a comprehensive AI/ML roadmap, leveraging SQL, R, Python, and cutting-edge Machine Learning algorithms. Bridged Data Science and business strategies, resulting in a remarkable 15% revenue growth.• Fostered a robust Data-Driven Culture, empowering the organization with a substantial 25% increase in data-informed initiatives.• Led a pioneering Multi-Channel Business Expansion strategy, seamlessly integrating with Amazon FBA and other marketplaces. Extended operations across 21 warehouses in eight states, spanning seven countries.• Revitalized ML Model Development, reducing Time-to-Market by an impressive 40%. Contributed to a notable 10% sales growth and 5% enhancement in Customer Satisfaction.• Championed Advanced Marketing Analytics, introducing ML-Based Customer Segmentation methodologies. Achieved a substantial 25% surge in customer engagement.• Architected a robust AWS Data Lake Infrastructure, empowering agile reporting, ensuring Data Governance Compliance, and elevating operational efficiency by an impressive 30%.• Orchestrated Performance Marketing Strategies, integrating Machine Learning and Marketing Analytics. Achieved a significant 15% boost in campaign ROI and optimal Return on Advertising Spend (ROAS).• Engineered a Data-Driven Marketing Campaign, leveraging strategic Audience Targeting, A/B Testing, and Uplift Modeling. Resulted in an exceptional 18% rise in Conversion Rates.• Effectively applied Agile project methodologies, leading to a 25% improvement in project execution efficiency.• Fostered Cross-Functional Collaboration, translating complex business requirements into high-value data science projects.• Strengthened Stakeholder Relations through insightful data visualization using Tableau and AWS QuickSight.
Anurag Yadav Education Details
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3.808/ 4.0
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7.23 / 10
Frequently Asked Questions about Anurag Yadav
What company does Anurag Yadav work for?
Anurag Yadav works for Grainger
What is Anurag Yadav's role at the current company?
Anurag Yadav's current role is Machine Learning Engineer.
What schools did Anurag Yadav attend?
Anurag Yadav attended Northwestern University, Rajiv Gandhi Prodyogiki Vishwavidyalaya.
Who are Anurag Yadav's colleagues?
Anurag Yadav's colleagues are Lawrence Paranidharan, Ravish M, Ziyun Huang, Jyothilakshmi S.
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