P B VAMSHI KRISHNA

Email: ad2z4y@r.postjobfree.com Mobile: +1-945-***-****

Professional Summary

Azure AI-100 certified professional with an analytical bent of mind offering chronicled success with nearly 10 years of extensive experience in Data Science, Data Engineering, Business & Data Analytics, Artificial Intelligence, Machine Learning, NLP, Computer Vision, Speech Recognition, Deep Learning and ETL across Finance, HR, Manufacturing, Energy, Oil & Gas and Retail domains

Talented Analyst with exceptional background in utilizing data from diverse information systems to develop tools, reports & models that help users access & analyze data resulting in higher revenues & margins and a better customer experience; competent in performing analysis of large data sets with the purpose of understanding or making conclusions for decision-making purposes.

Experienced in developing end-to-end solutions for business problems that involve the deployment of machine learning models. Proficient in the MLops(Machine Learning Operations) lifecycle, including model training, testing, deployment, and monitoring.

Demonstrated success in deploying machine learning models into production environments, ensuring seamless integration with existing systems. Skilled in utilizing platforms like Azure DevOps and GitHub Actions for continuous integration and deployment, enabling efficient and automated workflows in the MLOps pipeline also Hands-on experience with MLOps tools and platforms, including but not limited to NLP, Azure ML, DataRobot, MLFlow, and Kubeflow.

Notable success in analyzing trends on key business performance measures and identifying opportunities that result in additional revenue generation or cost reduction; detail specific individual with proven expertise in using analytical processes and techniques to improve and optimize information and decision systems

Insightful excellence in requirement gathering for enhancement while ensuring the optimal resolutions are achieved; capability in modeling data for business process management, executing quantitative & qualitative analysis that translates data into actionable insights through advance analytics like Linear Regression, SVM, PCA, KNN & Ensembling Techniques like Random Forest, XG Boost, CatBoost; neural networks like MX Net, Keras & PyTorch.

Showcased excellence in identifying areas of improvement in existing business by analyzing large-scale & high-dimensional data, interpreting problems and providing solutions to business problems using Data Analysis, Data Mining, Statistical Techniques & Machine Learning Models

Built strong relationships with various internal & external stakeholders to gain an understanding of their strategies, objectives, & tactics to develop a comprehensive corporate executive dashboard on Power BI & Tableau for trends recognition and analysis; managed Sentiment Analysis on NLP using Python & Artificial Intelligence

Effective leader and an Analyst, with a flair for adapting quickly to dynamic business environments and adopting pragmatic approach in improvising on solutions & resolving complex issues

CORE COMPETENCIES

Data Science & Analysis (ML, NLP & DL)

Service Delivery Excellence

Project Management

Requirement Gathering & Analysis

Business Analytics

Data Engineering, Data Mining &

Data Visualization

Statistical & Predictive Analysis

Strategic Planning & Implementation

Continuous Process Improvement/ Transformation & Automation

Risk Mitigation & Control

Team Management

Client Relationship Management

CERTIFICATION

Certification in Azure AI-100, in 2020

TECHNICAL SKILLS

Languages: Python, R, Linux Scripting

Tools: Python IDE, R Studio, Matlab, Tableau, Databricks, Azure, AWS (SageMaker, Glue, Redshift, EC2), Azure Cognitive Services, Azure ML-Studio, MS LUIS, GCP (Vertex AI, Big Query), DataRobot, Airflow and Spot Fire.

Frameworks: Flask, PyTorch, Keras, LLM’s (BERT, Transformers), Gen AI, OpenAI (ChatGPT-3.5 Turbo), Dockers.

Database: PostgreSQL, SQL, and Hierarchical/ Graph (AWS-Neptune)/ Relational/ ER Model/Document Database

Software: MS Office, MS Visio, Advanced Excel, Power BI, and Google Analytics

Operating System: Windows Servers, Linux

Big Data Platform: Hadoop, Spark (PySpark)

Compute Engines: CPU, GPU & TPU

Professional Experience

Dr. Reddy’s Laboratories Ltd Jul 22 to Present

Lead Data Scientist

Attribution Modelling: Evaluated marketing channel effectiveness through effort estimation, analyzing factors like engagement scores and interactions between medical representatives and healthcare professionals.

Utilized Python for code development and CatBoost Regression to create a predictive analytics model utilizing all available features gathered from diverse marketing channels and Shap values to identify the channel importance.

Integrated GCP MLOps practices, utilizing Cloud Build for version control, and implemented Airflow data pipelines to streamline data processing.

Leveraged Vertex AI Notebooks for model registry and GCP DevOps to automate model deployment and monitoring, ensuring real-time insights for marketing optimization.

Content Analytics: We're analyzing visuals used for doctor presentations to optimize their attractiveness and brand retention. Our prism tool assesses slide images against 9 essential criteria for effectiveness.

We utilized techniques like Python, Pytorch, OpenCV, ML, Gen AI (DALL-E, Mid Journey),Langchain and OpenAI techniques (LLM) to create a data-driven evaluation system.

Object Detection: Applied YOLO-v7 for object detection purposes.

Text Detection: Leveraged Paddle OCR for accurate text detection within images.

Image Transformation Techniques: Utilized OpenCV, Pillow and TorchVision for effective image transformation.

Color Analysis: Employed the KMeans algorithm to identify dominant colors within images.

Using Gen-AI (LLM’s) and Langchain developed prompts to create content for generating images from text.

Deployed the application on GPUs using GCP (Kubernetes Service) leveraging Docker. Implemented Git for Version Control and automated the CI/CD pipeline with GitLab to streamline Docker image creation and deployment using a Dockerfile.

Root Cause Analysis (RCA): Utilized ML techniques for Root Cause Analysis to identify poor-performing Headquarters. Analyzed performance metrics to pinpoint underlying reasons and develop targeted solutions for improvement.

Developed a predictive analytics model using XG Boost Regression, leveraging a comprehensive set of features collected from diverse activities of MR.

OCM Measurement (Market Mix Modelling): Led the development of an in-house application tailored for brand markets (e.g., Emerging Markets) to estimate the impact of diverse marketing activities on sales.

Utilized GLM Regression techniques and advanced statistical analysis to identify the impact of each marketing channel over the sales and forecasting the potential impact of future marketing activity mixes.

Utilized advanced statistical analytics and data science techniques for business consulting, extracting valuable insights that informed strategic decision-making and drove business growth.

Effectively led a cross-functional team of Data Scientists, Data Engineers, and Full Stack Developers, ensuring on-time project delivery and driving organic business growth across regions.

Technology Used: Python, Statistics, NLP (NLTK, Scipy), ML, DL, CV, Pytorch, Tensorflow, OCR, LLM’s, GCP Ecosystem(Vertex AI, Big Query, Cloud Build, GKS), GitLab, Dockers, Tableau.

The Math Company (Client: Mars Global Services) Sep 21 to Jul 22

Lead Data Scientist

Social Media Listening: Developed a flexible system for aggregating diverse social media data. Enhanced in-house models, expediting case resolution with an alert system. Built a dynamic real-time dashboard displaying live customer feedback and brand incidents

Processing substantial social media data volumes at a rate of approximately 30-40 million records per hour using Databricks.

Employed Delta Lake (Delta Tables) within Databricks to manage incremental data while utilizing Hadoop (Pyspark) for processing.

Created ML Models to identify Relavancy, Severity and Sentiment of Verbatims (XG Boost, GBM, CatBoost Models) & NLP (Word Embeddings like Glove, ELMO) on Azure Machine Learning Services.

Employed Git for efficient code and model version control, integrating CI/CD pipelines via Azure DevOps (Azure Kubernetes Service) for streamlined development. Leveraged Azure Data Factory for automated training, deployment, and monitoring, facilitating timely updates that enriched our R&D team's customer-centric decisions.

CA Comm Dashbord: Developed a dashboard to recommend effective content and identify optimal publishing platforms for maximizing post engagement. Improved messaging quality by leveraging successful past posts to drive higher engagement rates

For processing the extensive training data we are leveraging Hadoop (Pyspark) and Databricks to preprocess and fine tuning the model.

Fine-tuned cutting-edge LLM models like BERT and GPT for real-time content recommendations, amplifying content management, and engagement rates.

Created ML Models (XG Boost, Ada Boost) to predict the best platform for publishing the content and predict their engagement score.

Implemented Git for version control and Azure Kubernetes Service for seamless CI/CD pipeline integration, ensuring agile development.

Custom Tool: Developed a custom tool for a CPG company to understand shopping behavior through category sales performance.

Chatbot (Minerva): An in-house bot created based on NLP and ML Techniques that creates data visualizations on the fly and recommends business questions to the user.

Effectively worked on multi-functional roles encompassing people management, client delivery, and development.

Led a team of 3 Data Scientists, 2 Data Engineers & 3 Full stack developer to help a CPG client grow its retail business across different regions organically.

Technology Used: Python, Hadoop (Pyspark), NLP (NLTK, Scipy), ML, DL, Pytorch, Tensorflow, LLM’s (BERT, Transformers), Lang Chain, GIT, DataBricks, Azure ADF, Azure ML Studio, Power BI.

Coforge Technologies (Client: Lee Hecht Harrison) Jul 18 to Sep 21

Senior Data Scientist

ELLA: A chatbot that interacts with the candidates who receive a career transition services from LHH. It engages with the individuals in an intelligent, dynamic conversation to assist them in defining their job search criteria.

Applied LUIS and QNA Maker for precise entity and intent creation, enhancing the bot's conversational capabilities.

Implemented the application using Python as the primary programming language, ensuring efficient and scalable functionality.

Utilized various Azure components (Devops, Appservice, mointor) to develop a comprehensive end-to-end solution.

Recommendation Engine: Spearheaded the development of a Program Recommendation tool by leveraging Neo4j's graph database capabilities to analyze intricate user-program relationships.

Utilized data extracted from CRM Systems, establishing efficient data pipelines via AWS Glue Services for enhanced data processing.

Utilized user-user collaborative filtering and Cosine Similarity techniques to identify user similarities, optimizing program recommendations for career transitions.

Orchestrated model creation using AWS SageMaker and orchestrated a suite of AWS services (S3, SNS, SES, EC2) for streamlined storage, notifications, and deployment, bolstering system scalability and performance.

Fit4Next: Led the Fit4Next project, orchestrating AWS SageMaker for predictive modeling, AWS Glue for agile data processing, S3 for robust storage, EC2 for seamless app development, and integrated SNS and SES services for enhanced communication. This initiative aimed to create a Fit4Next scoring system, elevating precise candidate placement predictions.

Single-handedly managed the data extraction and transformation on Python, R, and AWS

Managed Optimizing NOx and SOx Emission & Controlling Fuel mixing for a Thermal Power Plant

Spearheaded multiple projects entailing:

Churn Analysis Prediction, Sentiment Analysis on Hotel Service Effectiveness and Chatbot for HR Queries for Finance, Hospitality and HR domains

Customer Lifetime Value Prediction and Air Flight Delay Prediction

Successfully utilized predictive modelling/ regression/ analysis/ processing/ cleansing techniques/ statistical analysis, along with model tuning & model comparisons and data visualization using Tableau & PowerBI

Utilized algorithms such as Linear & Logistic Regression, Decision Trees, Random Forest, XG-Boost, SVM, A-Priory, Segmentation and Time Series to deliver insights for the business

Explored new Data Science/ Machine Learning techniques for process improvement

Technology Used: Python, NLP, ML, DL, Pytorch, Tensorflow, LLM’s, GIT, AWS & Azure Components.

Sembcorp Energy India Ltd., Hyderabad as Sr. Executive (Energy Analyst) Nov 13 to Jul 18

Significant Highlights:

Demand Forecasting: Developed a robust time series model for forecasting coal demand at a thermal power plant. Applied methodologies like ARIMA, considering seasonal variations and external influences. Significantly improved operational efficiency through accurate predictions, optimizing inventory management, and ensuring uninterrupted power generation. Evaluated model effectiveness using metrics such as MAE and RMSE. Collaborated cross-functionally to implement data-driven strategies for enhanced coal procurement and usage.

Led data analytics for the prediction of future orders of the warehouse using multiple modeling techniques of time series forecasting using python

Performed analytics on congestion, IEX prices, and exchange sales using Python and ML

Managed performance monitoring and predicted PLA’s, auxiliary power consumption using python

Analysed & predicted Heat Rate, Calorific Values and Emissions using MatLab and Excel

Administered the entire gamut of Analytics for Power Trading in the Open Access, Energy Exchanges like (Indian Energy Exchange (IEX), Power Exchange India Limited) using Excel and Tableau

Role Across the Career:

Managing data analysis and processing activities involving analyzing, studying and summarizing data for extracting useful information which would assist in strategic decision-making and planning

Collaborating with cross-functional departments to understand company needs and devising possible solutions

Performing analysis & interpretation of results using standard statistical tools & techniques, pinpoint trends, correlations & patterns in complicated data sets; investigating data sets & trends for anomalies, outliers, trend changes, & opportunities

Presenting findings from the analysis and articulating any recommendations to the stakeholders; developing implementation plans to best help business derive value from the recommendations

Developing and implementing the group data science strategy; communicating strategy and analytic results in an actionable and non-technical manner to department leaders

Identifying & defining problem, designing approach, preparing, exploring, transforming & selecting data; building, validating, deploying model and monitoring & evaluating results

Driving organization to assist and predictive decision-making, unlocking the insights from customer & internal data, and presenting this in simpler ways for the teams

Managing complex structured and unstructured data sets from internal and external sources; creating and supporting models

Executing screen scrapping of unstructured data & building various domain business metrics to facilitate process improvement and re-engineering initiatives

Undertaking data cleansing activities, creating metadata standardization norms and periodicity of reports

Performing several roles like finding new process, determining gaps in existing process and implementing new processes

Analyzing impact of change with existing structure and implementing the same on the system with business.

Managing migration projects for smooth execution of all the pre & post implementation activities

Suggesting technology-based solutions for enhancing functional efficiency and achieving business excellence

Monitoring the processes for data intake, validation, mining and engineering as well as modelling, visualization, and communication deliverables; developing Data visualization reports on top of analytical database model for managers and stakeholders

JSW Energy Ltd., Tornagallu as Trainee Engineer (On Job Training) Aug 12 to Sep 13

PG Diploma in Power Plant Engineering from JSW Energy Center of Excellence

Education:

MBA in Intelligent Data Science from NIIT University, Neemrana, Rajasthan in 2020

B.Tech. (Electrical & Electronics) from JNTU, Hyderabad in 2012

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