AI/ML Associate Architect

Pm Pediatrics

1. Led design and development of AI solutions using TensorFlow, PyTorch, enhancing model accuracy significantly.
2. Translated business requirements into technical specifications, deploying Python-based recommendation systems that boosted user engagement.
4. Integrated Apache Kafka for real-time data streaming, facilitating seamless data flow across ecosystem components.
5. Designed microservices architecture with Docker and Kubernetes, ensuring scalability and high availability.
6. Optimized model training pipelines with scikit-learn for improved efficiency and reduced overfitting.
7. Analyzed large datasets with Pandas and NumPy, deriving valuable insights for data-driven decisions.
8. Migrated AI applications to AWS cloud, utilizing services like EC2, S3, and Lambda to cut operational costs.
9. Implemented OpenCV-based computer vision solutions for enhanced image classification and object detection.
10. Introduced Apache Spark for distributed data processing, significantly reducing processing time for large datasets.
11. Established CI/CD pipeline with Jenkins and Git, enabling smooth deployment of AI models.
12. Provided technical mentorship and conducted code reviews to ensure codebase quality.
13. Improved model interpretability with the integration of SHAP library.
14. Developed NLP models using NLTK and spaCy for sentiment analysis and named entity recognition.
15. Collaborated with domain experts to tailor AI solutions to specific business needs.
16. Ensured compliance with data privacy regulations through data anonymization and access controls.
17. Conducted performance profiling and optimization of AI algorithms, enhancing processing speed.
18. Actively participated in industry conferences and workshops to stay updated on AI/ML advancements.
19. Prepared comprehensive technical documentation including architecture diagrams and API guides.
21. Environment: TensorFlow, PyTorch, Python, Apache Kafka, Docker, Kubernetes, scikit-learn, Pandas, NumPy, AWS (EC2, S3, Lambda), OpenCV, Apache Spark, Jenkins, Git, SHAP, NLTK, spaCy, GDPR

Sr. Data Scientist

Amazon Web Services

1. Worked extensively with the Salesforce Service Cloud module, enhancing the capability of the customer support team through advanced analytics.
2. Developed intricate data models using SQL Server, enabling efficient data storage and retrieval. Conducted in-depth analysis of extensive datasets using advanced SQL queries, enhancing data-driven decision-making processes.
3. Designed and implemented business intelligence solutions with Tableau, creating interactive dashboards and reports for actionable insights. Utilized Git for effective Tableau workbook management.
4. Optimized ETL processes using Talend, improving data integration efficiency and reducing pipeline runtime. Employed Python scripting for customized data transformations, ensuring high data quality.
5. Implemented Git for version control, facilitating collaboration among cross-functional teams. Enforced Git branching strategies for streamlined code integration and release management.
6. Conducted statistical analysis using R, performing hypothesis testing and regression analysis on customer behavior data. Generated comprehensive reports using RMarkdown, driving marketing strategy adjustments.
7. Managed Oracle Database, overseeing schema design, user access, and performance tuning. Implemented backup and recovery strategies to ensure data integrity and availability.
8. Utilized Informatica for data cleansing and transformation, standardizing inconsistent data across various sources. Implemented data profiling routines to rectify anomalies, improving data quality.
9. Developed predictive models using scikit-learn, Python's machine learning library. Trained and validated models for customer churn prediction, achieving enhanced accuracy.
10. Optimized query performance in Microsoft SQL Server, employing indexing strategies and query plan analysis. Reduced query execution times significantly, ensuring faster data retrieval.
11. Created technical documentation using Confluence, detailing data workflows, ETL processes, and system architecture. Collaborated with cross-functional teams for comprehensive documentation.
12. Facilitated communication between technical and non-technical stakeholders, translating complex data concepts into understandable insights. Presented findings in meetings using PowerPoint, promoting data-driven decision-making.
13. Implemented data security measures in compliance with regulations, utilizing encryption techniques in Oracle Database and role-based authentication.
14. Utilized Red Hat Enterprise Linux as the operating system for server deployment, ensuring stable and secure hosting of database and analytics tools.
16. Environment: SQL Server, Tableau, Talend, Git, R, Oracle Database, Informatica, scikit-learn, Python, Confluence, PowerPoint, Red Hat Enterprise Linux.

Osmania University

Engineering