Sadhana Sainarayanan
MLOps & Platform Engineering| Data Science | Python | Carnegie Mellon University
- Role
- Analyst - Ml & Cloud Platform Engineering at Tata Consultancy Services
- Location
- Austin, TX, US
- LinkedIn followers
- 500 followers
About Sadhana Sainarayanan
During my time at TCS, I have productionalized several ML(time series forecasting, Classification, NLP) and optimization based pipelines for a FAANG Client. I have incorporated observability, and auto-instrumentation for python based applications. I collaborate with stakeholders to capture business requirements and explore the capabilities of the SAP BTP and Data Intelligence platforms to improve the performance of machine learning pipelines, web application security. I hold dual master\'s degrees from Carnegie Mellon University in Technology Innovation Management (Analytics) and Civil and Environmental Engineering (Advanced Infrastructure Systems). My education has equipped me with a wide range of skills, such as data analytics, machine learning, product management, and strategy management. I have a penchant for mobility data analytics and smart infrastructure, and I have applied my skills and knowledge in multiple internships and projects. I am a Google Cloud Certified Professional Machine Learning Engineer, Azure certified AI Engineer. I post my learnings on LinkedIn and write articles on Medium on key Data Science, Machine Learning and MLOps concepts and best practices. I discuss my takeaways, and I strive to share my knowledge with others. I am constantly seeking out opportunities to learn and grow in my field.TECHNICAL SKILLS:Software and Programming Languages: Python, R, SQL, Microsoft Excel(Pivot Tables, VBA, advanced formulae etc.), MATLAB, Postman (REST API), Docker, KubernetesCloud: GCP, Azure, SAP BTP Cloud, AWSMachine Learning: Clustering, Classification, Regression, Ensemble Methods, NLP (RNN, transformers), Reinforcement Learning (Foundational Knowledge), time series forcasting BI and Data Science: Tableau, Power BI, Spark, BigQuery, HDFS (Hadoop Distributed File System)MLOps: Monitoring (Grafana, Kibana, Splunk), Auto-Instrumentation/ observability(OpenTelemetry, Dynatrace), MLFlow, Explainability (SHAP), Fast APIAI Engineering: LLM, RAG, AI Agents, Model Evaluation (BLEU), Fine-tuning, MCPCI/CD: Jenkins, GitHub ActionsAjile: Scrum, Jira, Kanban boards, Gantt Charts, Project managementOperations Research: Linear Programming, Dynamic Programming, Stochastic Optimization (Gurobi)Infra Security: VIP, Web application Firewall (WAF)
Experience
Analyst - Ml & Cloud Platform Engineering
Nov 2023 — Present · Austin, TX, US
Instrumentation and Observability:Incorporated instrumentation and call tracing for applications using Dynatrace and Splunk to trace calls, and resource usage (CPU, Memory) metrics, enhancing traceability of latency, response times, and failures, which improved issue identification efficiency and informed development practices.Explored incorporation of Opentelemetry into python based applications.Monitoring:Established proactive monitoring systems, including automated alerts for non-fatal errors and metric based thresholds and cross-functional ticketing for critical application incidents, reducing response times by 50% and ensuring rapid issue resolution, leading to improved system reliability.Security:Incorporated role based restrictions in python applications. Implemented IP Filters and WAF Rules for applications with a UI. Orchestrated security configurations across 30+ projects, collaborating with 60+ developers and business leads to implement robust solutions and weekly tracking through Confluence and Jira, ensuring seamless go-live preparations and improved process efficiency.Accelerated the configuration setup by 80%, collaborating with the DevOps Team to improve the automation initiatives that reduced setup time from 5 minutes to under 1 minute by defining comprehensive requirements, providing feedback, and troubleshooting code, optimizing project timelines.AI- Building an AI agent to perform all security actions discussed above- Incorporating a multi client tool with an MCP component to reduce the need for manual effort while performing actions such onboarding, configuration updates, incident resolution, production changes.Client: Big Tech (FAANG)
Education
Carnegie Mellon University
Master of Science - MS, Engineering and Technology Innovation Management (Analytics)
2019 — 2021
SSN College of Engineering
Bachelor of Engineering - BE, Civil Engineering
2015 — 2019
Carnegie Mellon University
Master of Science, Civil and Environmental Engineering (Advanced Infrastructure Systems)
2019 — 2021
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