KALYANI MULLAPUDI
Summary
A performance-drive & highly accomplished Data Scientist with an extensive background of 15 years in Data Science, specializing in Statistical Analysis, Machine Learning, Computer Vision, Generative AI, and large language models. Demonstrated elevated level of proficiency in applying supervised and unsupervised data mining techniques, currently contributing as a Data Scientist, acquiring in-depth industry knowledge and skill development. Illustrated profound expertise in optimization, probability theory, queuing theory, game theory, simulation, multi-criteria decision analysis, stochastic models, system dynamics, forecasting, and mathematical modeling, with a history of developing and implementing algorithms tailored to business needs, rigorously tested on extensive datasets. Proven acumen in simulating, designing, developing & deploying computationally complex and practical data; built and delivered comprehensive data strategy roadmap; ensured final deliverables were of the highest quality. Leveraged comprehensive proficiency in developing advanced Machine Learning algorithms and statistical methods, including regression, scenario analysis, modeling, clustering, decision trees, neural networks, and more, with a focus on enhancing accuracy. Data Evangelist with the capability to deliver valuable insights through advanced data-driven methods like Exploratory Data Analysis, Data Science, Machine Learning Modelling, Deep learning, Data Engineering, Business Statistics, Algorithms, Data Quality Assessment, Data Architecture, Data Design, Modelling & Solution, and other techniques. Track record of establishing cordial relationships with clients, stakeholders & technical teams for successfully executing concurrent projects; skilled in delivering pre-sales support and driving process re-engineering & streamlining. A visionary leader, training teams in data science and Python, facilitating effective knowledge transfer, with profound expertise covering a wide array of statistical and machine learning algorithms and packages, contributing to data-driven success. Exceptional team player and creative problem solver with outstanding communication, analytical, interpersonal, and rapid learning abilities. Committed to acquiring in-depth knowledge in new areas.
Overview
17
17
years of professional experience
1
1
Certification
Work History
AI Pre Sales Manager - Generative AI Specialist
CVS
Illinois, USA
10.2021 - Current
- Build and maintain generative AI and processes for business systems (Customer Engagement and contract Management) for services the global team implements to maintain world-class it service delivery
- Conducted in-depth requirement gathering sessions with clients to ensure alignment between business needs and proposed data science initiatives, enhancing customer satisfaction by 40%
- Led cross-functional teams in the design and demonstration of data science product prototypes, significantly improving proposal acceptance rates by 35%
- Collaborated with marketing to create impactful case studies and white papers, increasing lead generation by 20% through targeted content marketing strategies
- Implemented consultative selling techniques, establishing long-term relationships with key clients and positioning the company as a trusted advisor in data science solutions
- Negotiated and closed deals with strategic accounts, contributing to a 15% growth in annual revenue
- Stayed abreast of the latest trends in data science, machine learning, and AI, applying this knowledge to innovate and improve the solution portfolio offered to clients
- Facilitated client education workshops on the benefits and applications of data science, enhancing client engagement and project buy-in
- Played a pivotal role in project scoping and cost estimation, ensuring projects were delivered within budget and exceeded client expectations
- Engineering a predictive model to pinpoint potential platinum user upgrades, catalyzing revenue growth
- Recruited because of outstanding performance and reputation at previous positions to build and drive growth in the Advanced Technology Solutions Architect Team, Technical Delivery, Professional Services, Customer Success Team, TAM Organization, Program Management and Global Customer Support/Team
- Lead 33 team members as the technical account resource for clients and participated in operations, presales/post-sales activities to lead executives to consensus and plan Global engagements for the proper business solutions
- Manage TCV (Total Contract Value) of $50M+ by using tactical planning, rigor and discipline in solution design and service design and ensuring the customer requirements are 100% met while attaining the financial objectives
- Improve employee work performance by hiring, evaluating, and coaching technical employees, including customer-facing Sales Engineers, Program Managers, and Solutions Sales Experts
- Be the voice of the customer
- Keeping a high NPS of 94% with Customer Advocacy by ensuring a world-class customer experience and customer satisfaction
- Extensive business acumen and knowledge of risk management, root cause analysis, problem detection, team management, client services and account planning
- Ensure client relationships & project success by prioritizing tasks & building Agile best practices, security solutions, TAM relationships with local and technical staff to provide quality results on all technical services & oversee RFPs, SOW’s RFI’s, technical services, customer meetings, quality assurance (QA)
- Increase sales; delivery by 28% month-over-month by developing standards of work (SOW) and collaborating with sales teams on requests for proposals/quotes/information (RFP/RFQ/RFI) that require solutions team participation
- Financial management and mitigation strategies (risks) were key to success with the business relationships
- Optimize financial performance (P&L), ensure profit margins of 35% by devising actionable strategies for staff utilization, change management, sales architects, service delivery, and client satisfaction
- Employed a comprehensive assessment approach incorporating Holistic Evaluation of Language Models (HELM), LORA, QLORA, chainlit, pinecone, weaviate, LangChain, LlamaIndex, Retrieval-augmented generation (RAG), llama 2, falcon, Amazon Bedrock, Amazon Titan foundation models, and llma2 to construct the 'Search' and 'Summarize' models for CVS
- Successfully deploying a sophisticated chatbot leveraging LLM to elevate customer interaction and support
- Collaborating with the data engineering team to implement advanced data preprocessing techniques, ensuring data readiness for machine learning models
- Conceiving & deploying deep learning model to target potential customer upsells, significantly contributing to revenue amplification
- Seamlessly integrating Flask RESTful services with Angular services within the application to provide a user-friendly experience
- Producing meticulous program specifications documentation and adeptly collecting requirements, fostering clear project comprehension and management
- Monitoring daily task progress & promptly resolving team member issues, ensuring the punctual achievement of the project milestones
- Engineering and deploying a potent Deep Neural Network to forecast customer churn, fortifying customer retention efforts
- Implemented Airflow's monitoring and alerting features to ensure the timely detection and resolution of workflow failures, enhancing reliability and scalability
- Personalized User Experience: By employing recommendation systems, we've been able to offer highly personalized content to users
- This not only improves user engagement but also increases the likelihood of conversion, as users find what they need or discover new interests
- Feedback Loops for Continuous Improvement: We've established robust feedback loops that continuously improve our recommendation models
- User interactions and feedback are analyzed to adjust and refine the recommendation algorithms, ensuring they remain relevant and effective
- Privacy and Ethical Considerations: In deploying these systems, we've been mindful of privacy and ethical concerns
- Our models are designed to respect user data privacy and avoid biases that could skew recommendations in an unintended way
- Cross-Functional Collaboration: Implementing these systems required cross-functional collaboration between data scientists, engineers, and product managers
- This ensured that the recommendation systems were well-integrated with the product and aligned with business goals.
Data Scientist
HSBC
Hyderabad, India
11.2016 - 10.2021
- Analyzed tens of thousands of daily data points to identify potential malware threats, with a focus on machine learning techniques to counter evolving evasion tactics
- Identified and addressed gaps in existing business rules through the application of predictive analytics to improve fraud detection
- Built association rules to identify potential fraud cases and enhance fraud detection
- Utilized clustering techniques to categorize providers based on their fraud risk scores, enabling more targeted fraud mitigation
- Ranked worker compensation providers based on various features to reduce the fraudulent activities and improve the overall efficiency
- Detecting and predicting outages, enhancing Smart Grid security and theft detection, improving operational efficiency through machine learning, and aligning team targets with the client's business objectives are all important aspects of our strategy
- Monitoring daily tasks and ensuring the achievement of the project milestones
- Implemented MLOps best practices to streamline the end-to-end machine learning lifecycle, by ensuring reproducibility and scalability
- Analyzed tens of thousands of daily data points using Python to identify potential malware threats, leveraging Python's robust libraries for machine learning techniques to counter evolving evasion tactics
- Utilized clustering techniques to categorize providers based on their fraud risk scores, enabling more targeted fraud mitigation
- Ranked worker compensation providers based on various features to reduce fraudulent activities and improve overall efficiency
- Implemented an NLP system to automatically extract and categorize key information from financial documents
- The project involved named entity recognition and relationship extraction using SpaCy and custom training datasets
- This system streamlined the document review process, saving significant time and reducing human error.
Sr SAS Developer
Mahindra Satyam
01.2013 - 08.2016
- Detected various fraud scenarios by analyzing claims data, including geo-location patterns, location-specific frauds, duplicate billing, upcoding, and excess modifier usage using SAS
- Closely interacted with business stakeholders on requirement clarifications, test approval etc
- Drove the defect triage calls involving various end-to-end vendor systems
- Performed financial management and ensured that the projects are delivered within the budget
- Performed risk-issue management and handled stakeholders
- Performed reporting to the client management team with the right metrics
- Extensively used Jira and SharePoint for requirement management, test management, risk-issue-action.
SAS Developer
Satyam Computers
06.2007 - 12.2012
- Closely interacted with business stakeholders on requirement clarifications, test approval etc
- Drove the defect triage calls involving various end-to-end vendor systems
- Performed financial management and ensured that the projects are delivered within the budget
- Performed risk-issue management and handled stakeholders
- Assisted in the development and maintenance of SAS programs for data manipulation and reporting purposes
- Conducted data profiling and validation to ensure data accuracy and integrity in adherence to industry standards
- Participated in the design and implementation of SAS Enterprise Guide projects, improving workflow efficiency
- Collaborated with team members to troubleshoot and optimize existing SAS code, resulting in a 25% improvement in program performance.
Education
MBA (master’s in business administration) -
Bachelor of Computer Science -
Skills
- Strategic planning and execution
- Project Management
- Artificial Intelligence
- Data Science & Modelling
- Reporting & Dashboard
- Cross-functional collaboration
- Statistical Analysis
- Client & Stakeholder Management
- Requirement Gathering & Analysis
- Predictive Modelling
- Machine Learning
- GENERATIVE AI
- Change Agent
- Collaborator
- Communicator
- Innovator
- Planner
- Thinker
- Proficient in data science methodologies, tools, and technologies with the ability to design effective solutions Strategic Selling: Expert in consultative selling approaches and negotiation, with a track record of successfully closing deals Communication: Strong presentation and communication skills, capable of explaining complex data science concepts to non-technical stakeholders Collaboration: Experienced in leading cross-functional teams and working collaboratively with internal and external stakeholders Continuous Learning: Committed to staying informed on industry trends and leveraging new knowledge to drive innovation and solution improvement
Certification
- Generative AI & Large Language Models: Generative AI with LLMS, Generative AI for Everyone (deeplearning.ai), Databricks: Large Language Models: Application through Production, LLM: Foundation Models from Ground Up
- Machine Learning: Machine Learning (Coursera, Stanford Online), Structuring Machine Learning Projects (Coursera, deeplearning.ai), Microsoft Certified Azure Data Scientist Associate.
- Deep Learning: Improving Deep Neural Networks: Hyperparameter Tuning, Regularization, and Optimization (Coursera, deeplearning.ai), Convolutional Neural Networks (Coursera, deeplearning.ai)
Personal Hobbies
Reading, Crosswords and Movies.
Academic Qualification
Bachelor’s in computer science. 2004. India. Master’s in business administration. 2007. India.
Technical Skills
Amazon AWS | Microsoft Azure | R | SAS E-Miner | SPSS | Python | SAS, Oracle | SQL Server | MongoDB | Tableau | SAS Visual Analytics | Power BI | PostgreSQL | Docker | Jenkins | AWS | GIT | CI/CD Pipeline | Kubernetes | Grafana | Snowflake | Qdrant Vector Database | Chromadb, T-test | Anova | Manova | Linear Regression | Logistic Regression | Regularization (Lasso, Ridge, Elastic Net) | k-Nearest Neighbors (k-NN) | k-Means | Decision Tree (CART, CHAID) | Ensemble Methods (Random Forest, Gradient Boosting, Bagging, AdaBoost) | Dimensionality Reduction (PCA, Factor Analysis, Matrix Factorization) | Recommendation Systems | Support Vector Machines (SVM) | TensorFlow | NumPy | SciPy | Pandas | Matplotlib | Seaborn | OpenCV | Theano | Keras | PyTorch | Spacy | Pytesseract, Image Classification (CNNs, Inception V3, GoogLeNet, VGGNet, ResNet, DenseNet, LeNet, AlexNet) | Object Detection (R-CNN, Faster R-CNN, YOLO, SSD) | Object Tracking (Stacked Autoencoders, MDNET, GOTURN, ROLO) | Semantic Segmentation (DeepLab, DeepLab3+, ParseNet, FCN) | Instance Segmentation (Mask R-CNN, R-CNN) | Optical Character Recognition (OCR) | Named-Entity Recognition (NER) | Generative Adversarial Networks (GANs) | Image Captioning | Bag of Words | Word Embeddings | Text Classification | Language Modeling | Machine Translation | LSTM | GRU |BERT | Huggingface Transformers | Holistic Evaluation of Language Models (HELM) | LORA | QLORA | Chainlit | Pinecone | Weaviate | LangChain | LlamaIndex | Retrieval-Augmented Generation (RAG) | Llama 2 | Falcon | Amazon Bedrock | Amazon Titan Foundation Models
Personal Information
Date of Birth: 09/24/1983
Languages
English, Telugu, and Hindi.
Timeline
AI Pre Sales Manager - Generative AI Specialist
CVS
10.2021 - Current
Data Scientist
HSBC
11.2016 - 10.2021
Sr SAS Developer
Mahindra Satyam
01.2013 - 08.2016
SAS Developer
Satyam Computers
06.2007 - 12.2012