Machine Learning- Philadelphia, USA Chapter – Data Science for Climate Change: Reducing energy consumption of buildings (part 2)

Python Functions for Data Science

Statistical Analysis for Genomic Data Science

Git and Web Development

SQL (Basic) Certificate

Coursera_R shiny to plot gene expression

Generative AI: Fundamentals, Applications, and Challenges

AI Security and Governance

As part of a team initiative to equip individuals with the skills and knowledge needed to secure roles in data science, analytics, and machine learning, I mentored, instructed, and developed comprehensive materials for 12 aspiring data scientists, data analysts, and machine learning practitioners through a non-profit organization.

Data Science and Data Analytics Freelance Instructor

Actively involved in leading bioinformatics, data science, and AI efforts with WashU oncologists to advance Clinical Oncology research [ORCID: 0009-0009-0579-7470]

Bioinformatics and data Science Cancer researcher

Spearheading an end-to-end predictive analysis project, from data collection and preparation to model development, evaluation, and deployment, to forecast key business metrics and provide actionable insights for decision-making

Lead Data Scientist and Project Lead

Designed and implemented RNA-seq and proteomics pipelines, utilizing DESeq2, edgeR, and limma for differential expression analysis, integrating pathway enrichment analysis (GSEA, Reactome) to enhance biomarker discovery and drug target validation to study the etiology of Alzheimer's Disease.

Research Scientist (Bioinformatics and Data Science)

- Developed scalable ETL pipelines using Python, SQL, PySpark, and Airflow for fraud detection and customer retention, improving
fraud detection precision and reducing data processing time by 10%
- Designed a centralized data lake with AWS S3, Glue, and Redshift, integrating government invoices, FOIA reports, and competitive
intelligence, boosting data accessibility by 60%.
- Led Agile sprint planning and cross-team collaboration for data warehouse development, improving deployment speed by 30%.

Business Data Scientist 

- Developed predictive models using Centene’s TruCloud claims data, applying XGBoost, Random Forest, and feature engineering techniques to identify cost drivers. Reduced inefficiencies by 18%, contributing to $500M in savings.
- Built real-time KPI dashboards for claims performance using Power BI, SQL, and AWS Redshift, automating reporting workflows and improving strategic visibility by 48%.
- Optimized Medicare & Medicaid claims processing by developing workflow automation pipelines with Python, SQL, and Airflow, reducing manual interventions and increasing efficiency by 18%.
- Led and mentored a team of 3 data scientists, improving data standardization, feature engineering, and A/B testing of dashboards, enhancing model accuracy and operational efficiency.

Sr. Consultant (Data Science/ Data Analytics/ Business Analysis  - Product Owner)

- Developed LLM validation pipeline for real estate document automation, leveraging GPT-4, Llama-2, and Falcon with custom
tokenization & prompt engineering. Improved accuracy by 20%, reducing manual legal reviews and accelerating risk assessments.
- Led AI-powered document parsing initiatives, aligning underwriting, risk management, and legal teams with automation goals,
streamlining transactions, and reducing operational bottlenecks.
- Optimized JIRA workflows by integrating claims analytics dashboards, automating sprint tracking and backlog prioritization.
- Designed custom workflow alerts, boosting delivery efficiency by 25%

Sr. Consultant (Data Science/ Data Analytics/ Business Analysis)

Next Generation Sequencing, DBMS, Statistical Analysis, Machine learning, Deep Learning, Cloud Computing

Research Assistant and Data Analyst (Bioinformatics and Data Science)

Coordinator of Sciences, Data Analyst, and Educator 

- Led a cross-functional team at AI Alignment Liaison, contributing expertise in Data Science, AI Ethics, and Responsible AI Innovation.
- Provided strategic guidance to steer the project direction toward responsible, human-aligned AI development.
- Applied data science methodologies to support AI safety and ethical decision-making initiatives.
- Championed responsible innovation practices to enhance transparency, fairness, and accountability in AI systems.
- Collaborated with multidisciplinary stakeholders to align AI outputs with societal values and ethical standards.
- Demonstrated leadership and thought partnership during a pivotal growth phase of the open-source project.

Team Lead — Data Science, AI Ethics, and Responsible Innovation

- Systematically reviewed research papers in Responsible AI domains (Fairness, Transparency, Explainability, Robustness, Accountability) to extract practical, operationalizable principles.
-Developed modular Python components to translate these principles into reusable, plug-and-play building blocks for integration into future AI governance systems.
-Authored clean, well-documented code outputs enabling explainability workflows, including bias detection, feature attribution, and transparency metric computation.
-Designed and maintained a structured bi-weekly development and delivery workflow, anchored by a dynamic “Master Index” linking academic sources to corresponding implementation assets.
-Standardized input-output schema across components to ensure reproducibility, scalability, and ease of integration across varied use cases.
-Actively contributed to internal knowledge-sharing forums, presented progress updates, and iterated based on multidisciplinary feedback to align deliverable

AI Consultant - Strategic Planning, Execution & Evaluation of RAI & XAI Frameworks

Driving Business Impact by Designing, Architecting & Building Generative AI Agents | AI Strategy & Product Leadership

Know about Suneeta Modekurty's work experience, education, and much more. Suneeta Modekurty