LAVANYA LAKSHMAN

Currently leading the design and development of scalable, cloud-native data and AI solutions powering enterprise-grade talent intelligence platforms within Accenture’s Skills.AI Human Capital Analytics team. Participate in Human Capital Analytics Data Science & Engineering Team hiring, induction and mentorship programs, represent Human Capital Analytics team during client oral sessions at Bangalore Office.

• Led AI-powered solution development to future-proof corporate talent strategies. Oversaw and implemented the full lifecycle from architecture to deployment, including workforce data ingestion, labor market insights, and ML/AI integration.
• Designed and implemented cloud-native data pipelines on AWS and Databricks for AI-driven workforce analytics platforms.
• Developed repeatable frameworks for ingesting and transforming large-scale datasets using AWS Glue, S3, Athena, and Lake Formation.
• Led cross-team initiatives to modernize legacy data pipelines into scalable, modular components reducing tech debt.
• Designed organizational architecture standards for Talent Hub data platform including self-service dashboards, modular ETL jobs, and alerting frameworks using CloudWatch.
• Integrated external third-party APIs and legacy systems into AWS-based lakehouse architecture, ensuring data lineage and schema evolution.
• Developed ML-Ops pipelines with model accuracy tracking and monitoring using SageMaker and MLflow.
• Delivered enterprise-level data modeling frameworks consolidating 15+ sources into a single source of truth.
• Built robust API orchestration frameworks integrating 10+ external APIs for workforce benchmarking, skill demand forecasting, and market insights.
• Built APIs for consumption layers and orchestrated microservices deployment using AWS Lambda and API Gateway.
• Delivered advanced analytics and machine learning solutions by providing curated, clean, and governed data.
• Drove internal process improvements and reusable asset creation, contributing to faster and more consistent product deployments.
• Spearheaded cloud architecture improvements to support multi-tenant ingestion and external partner integrations to productionize ML pipelines and integrate outputs with downstream analytics platforms.
• Conducted market research and EDA to support client strategy, identify trends, and drive digital transformation outcomes.
• Implemented ML-Ops pipelines for multi-model accuracy tracking and governance using modular AWS Glue jobs and containerized ML deployment.
• Engineered similarity-matching algorithms to dynamically identify top-N job roles, improving delivery efficiency and reducing manual validation.
• Developed and deployed RESTful APIs using AWS Lambda, API Gateway, and ElastiCache, supporting low-latency UI integrations and real-time data access.
• Led full API lifecycle management including design, deployment, versioning, exception handling, and integration.
• Successfully delivered end-to-end solutions by collaborating with cross-functional teams across data, engineering, and business stakeholders.
• Co-created product concepts embedding AI and GenAI capabilities into enterprise-ready applications to recommend future-state roles and skill gaps for organizations.
• Built large-scale entity extraction workflows for labor market and workforce datasets, enabling job role classification, skill taxonomy mapping, and demand-supply insights.

• Developed AI-powered frameworks for talent strategy and upskilling, including the design of role transition pathways and career recommendation logic using LLM-based skill ontologies.
• Led the development of job-role recommendation and workforce calibration models, including logic to compute upskilling, hiring, and retention actions at scale across workforce segments..
• Created dynamic analytics pipelines for transforming and modeling workforce datasets, automating insights generation and maturity scoring of client talent strategies.
• Built reusable programs to recommend similar and adjacent skills for role transition paths, incorporating logic based on demand-supply skill ranking, relevancy scores, and skill type weightage.
• Developed Role-Recommender and Workforce Calibration logic by introducing automation, parameter tuning, and generalization to support cross-client scalability.
• Designed and developed NLP and ML models to predict and forecast role and skill gaps, trends and corporate workforce projection at scale.
• Led dashboard storyboarding, insight packaging, and presentation of analytics outcomes to senior client stakeholders, partnering closely with leadership for delivery excellence.

• As a core member of Risk Innovation & analytics team, led the team & engaged with the functional stakeholders to understand the client requirements as well as ideating on the solutions to mitigate risk associated with the business process associated with leading UK based banking client.
• Developed an automated web application to process HR data for UK based banking clients using Python, Flask and PostgreSQL (data storage). Automated the process of manual checks and FTE calculation and forecasting which increased the operational efficiency by 90%.
• Built a Loan Recommendation engine to predict feasibility of lending loan. Used statistical EDA methods for data analysis and preprocessing, PCA technique and ML algorithms Logistics Regression, SVM classifier, Random Forest, XG Boost.
• Built classification models using SVM to create page landing models to land on page in pdf, QA bots, text classification and sentiment analysis models as generic solutions for banking clients.
• Designed end-to-end systems integrating data extraction, transformation, and storage using Python, PostgreSQL, and web scraping techniques. Built scalable solutions for FTE allocation, task optimization, and PDF data parsing, laying the foundation for automated workflows and ML integration.
• Leveraged Python for FTE forecasting and MI insights generation from HR data; applied NLP techniques (Gensim similarity, NER) to extract meaningful keyword-driven content from documents.

• Contributed to full project lifecycle: requirement gathering, Oracle PLSQL & Forms development, data processing, and deployment.
• Delivered key projects including Financial Integration (ACCPAC) and insurance product systems, managing third-party server integrations with financial implications.
• Demonstrated strong skills in Oracle technologies, application development, and client delivery for organizations like MEA Insurance, Landmark Group, Tata Communications, and Tata Capital.