Professional Background
As a Data Scientist at UPMC, I collaborate with the Transplant Quality Team to use data analytics to enhance patient outcomes. Building Power BI dashboards, statistical modeling, and healthcare analytics are the main focuses of my work. In order to provide data-driven insights that improve transplant quality and patient care, I work directly with surgeons, medical professionals, administrators, nurses, directors, and managers.
Previous Experience:
Data Analyst & Data Manager – Developed Tableau dashboards, integrated APIs using Python, performed ETL with Alteryx, optimized Python scripts for faster data retrieval, and worked with JIRA for issue tracking.
Student Researcher – Focused on OpenStreetMap (OSM) data and geospatial Python libraries (OSMnx), developing shortest path algorithms to enhance accessibility for disabled individuals.
Technical Support Engineer – Managed ticketing systems using Salesforce Service Cloud, assisted university staff and students, resolved IT issues, and provided timely follow-ups to ensure efficient support.
Senior Software Engineer at Capgemini – Worked on monitoring tools, KPIs, CI/CD pipelines, automated tasks with Python, managed Microsoft SQL Server, handled shift operations, and ensured seamless application testing.
I enjoy tackling challenging issues and developing data-driven solutions as a software engineer and data science specialist. I adore learning about and experimenting with new technologies since I'm a tech geek.
About Sharika Loganathan
My Education
MS in Information Science, University of Pittsburgh
(2022-2024)
GPA: 3.8
BE in Computer Science & Engineering, Visvesvaraya Technological University
(2016 – 2020)
GPA: 3.2
My Skills
Programming & Development: Python, R, JavaScript, Flask, Angular, HTML/CSS, Tailwind CSS
Machine Learning & AI: Generative AI, NLP, Deep Learning, BERT, Bayesian Models, SVM, DNN, KNN, Prompt Engineering
Data & Cloud: SQL, MongoDB, Elasticsearch, AWS SageMaker, Linux, AWS, Azure
Data Visualization: Excel, Power BI, Tableau
VOLUNTEERING
Women Tech-makers Ambassador
Jul 2023 - Present
Student Information Technology subcommittee Member
University of Pittsburgh Student Affairs
Jan 2023 - Present
Student Mentor
CGI
Jan 2023 - Jun 2023
Campus Business Manager
PrepBytes
Jul 2020 - Sep 2020
Event Coordinator
Computer Society of India
Feb 2018
CERTIFICATIONS
Salesforce Certified AI Specialist
Issued Oct 2024
Salesforce Certified AI Associate
Issued Nov 2023
Salesforce Certified Associate
Issued Jul 2023
Microsoft Certified: Azure Fundamentals
Issued Sep 2021
WORK EXPERIENCES
Data Scientist - UPMC
Clinical Data Analytics & Insight Generation
- Collaborate with the Transplant Quality Team to identify actionable insights for improving organ transplant outcomes and operational efficiency.
- Developed and maintained Power BI dashboards for real-time tracking of transplant metrics, optimizing decision-making for clinicians and administrators.
- Performed statistical modeling and trend analysis to support transplant program evaluation and compliance with UNOS and CMS standards.
Predictive Modeling & Research Support
- Built predictive models to forecast transplant volumes, donor-recipient matching outcomes, and organ discard risks.
- Contributed to research protocols including Kaplan-Meier survival analysis, Cox proportional hazards modeling, and donor-recipient outcome studies.
Data Pipeline & Quality Improvements
- Enhanced data integration processes reducing data discrepancies and improving accuracy in transplant datasets.
- Led efforts to identify phase duration metrics, automate error tracking, and minimize data quality issues across multidisciplinary datasets.
Stakeholder Collaboration & Communication
- Work closely with surgeons, nurses, and directors to translate clinical requirements into data solutions.
- Acted as a bridge between technical and non-technical teams, ensuring stakeholder alignment on dashboard design, data definitions, and performance metrics.
- Participated in policy-focused initiatives such as the Increasing Organ Transplant Access (IOTA) Model webinar and related measure development.
Tools & Technologies
- Expertise in Python, R, SQL, Power BI, Tableau, EPIC Clinical Analytics
- Experience in cloud platforms (Azure, AWS,Salesforce) and tools like JIRA and GitHub for data tracking and version control.
SOFTWARE ENGINEER - CAPGEMINI OCT 2020 - AUG 2022
Service Excellence & Incident Management
- Resolved over 2,000+ incidents across platforms like SCOM, CA, ServiceNow, Azure, and JIRA, enhancing incident response efficiency and improving customer satisfaction by 35%.
- Ensured 100% SLA adherence, timely ticket assignments, and maintained accurate shift handovers with proactive communication and escalation procedures.
Process Optimization & Software Reliability
- Improved unit test coverage by 40%, contributing to better test-driven development and increased system reliability.
- Enhanced SQL-based ETL processes, reducing processing time by 10% and improving data quality for CRM and financial reporting systems.
Automation & Infrastructure Monitoring
- Worked with Azure databases and health dashboards, automating repetitive tasks and identifying system trends for proactive issue resolution.
- Supported alerts and ticket workflows, reducing false alerts and improving overall infrastructure stability.
Compliance & Quality Control
- Achieved zero incident quality errors and maintained >98% compliance across key metrics including incident updates, email response time, and change management processes.
- Maintained full adherence to internal processes (FCO, GAB/GIR/IAM) and participated actively in quality improvement discussions and audits.
Learning & Development
- Completed 40+ hours of technical and soft skills training, achieving Sigma Level 3 and LEAN Score 3 compliance.
- Contributed to process automation, knowledge sharing, and cross-training, while proposing SIP and A3 initiatives to improve service delivery.
Leadership & Collaboration
- Participated in operational calls, team discussions, and client engagement forums with consistent contributions to SIP, process improvements, and knowledge-sharing initiatives.
- Maintained 100% participation in surveys, timesheets, training modules, and internal compliance protocols.
SOFTWARE ENGINEER INTERN JAN 2020 - MAY 2020
- Leadership & Coordination
Acted as the primary point of contact for a cohort of 23 students, liaising between Capgemini's Learning & Development (L&D) team, trainers, and senior managers. Monitored training schedules, attendance, and addressed team-level concerns to ensure smooth program execution.
- Collaborative Engagement
Collaborated closely with team leads and senior managers to identify areas of improvement and optimize learning outcomes during the internship.
- Technical Training – Hands-On Exposure
Completed extensive hands-on training across key IT domains:
- Windows Essentials & Fundamentals (Windows Server 2012 R2)
- Linux Essentials & Fundamentals (RHEL 7)
- Networking Essentials (Cisco Packet Tracer, ACLs, Routing, Subnetting)
- Database Fundamentals (Microsoft SQL Server)
- Application & Storage Fundamentals
Projects
Her Health Advocate – Digital Health Platform
BERT-Based Interactive Document Retrieval & Q&A System
BERT-Based Interactive Document Retrieval & Q&A System
Developed a digital health platform with HTML/CSS/JS, Flask, JWT authentication, MongoDB, and ChatGPT API, leading to a 30% increase in user engagement.
BERT-Based Interactive Document Retrieval & Q&A System
BERT-Based Interactive Document Retrieval & Q&A System
BERT-Based Interactive Document Retrieval & Q&A System
Created a document retrieval system using BERT, Angular, and Tailwind CSS, with a backend powered by Flask, Celery, Redis, and Elasticsearch for efficient real-time data interaction.
Corrosion Rate Prediction Using Machine Learning
BERT-Based Interactive Document Retrieval & Q&A System
Differential Privacy in Big Data Classification with Deep Learning:
Trained multiple ML models (Bayesian, SVM, DNN, KNN) to predict corrosion rates, reducing incidents by 20% through data-driven insights.
Differential Privacy in Big Data Classification with Deep Learning:
Differential Privacy in Big Data Classification with Deep Learning:
Differential Privacy in Big Data Classification with Deep Learning:
Enhanced classification accuracy by 15% using Epsilon Differential Privacy, leveraging Python libraries like Pandas, Scikit-learn, Pytorch, TensorFlow, and Keras.
Full Stack Development Projects
Differential Privacy in Big Data Classification with Deep Learning:
Full Stack Development Projects
Publication and Conferences
Comprehensive Study of Differentially Private Deep Learning Mechanism
NATIONAL CONFERENCE ON EMERGING TRENDS IN ENGINEERING SCIENCE FOR FUTURE TECHNOLOGY
Aug 1, 2020
Conference
1st National Conference on Emerging Trends in Engineering Science for Future Technology (NCETESFT-2020)
Achievements
James G. Williams Scholarship Fund
School of Computing and Information 04/2024
Second Place, She-Innovates Hackathon
School of Computing and Information 02/2023
Capturing moments
Contact Me
Hey everyone!
I've been getting a lot of DMs for guidance, so decided to take action on it.
I'm excited to help folks out and give back to the community via Topmate. Feel free to reach out if you have any questions or just want to say hi!
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