Josephine Gnanaraj

Email : ad25kx@r.postjobfree.com Durham, NC-27705 gnanaraj-995863190/ Experienced data scientist with approximately five years of professional expertise in crafting secure, cost-effective, innovative data solutions, implementing and fine-tuning machine learning models to enhance accuracy and to drive actionable solutions. HANDS ON SKILL SET:

Tools : Azure(ADLS, ADF, VM, Synapse, AKS, DevOps, Airflow, Databricks), Spark, Hadoop, MS Excel, SQL Server Languages: Python, R, SQL Orchestrating Tools: SVN, GIT, Jira Viz tools: Tableau, Python libs ML Tools: Pandas, Numpy, Sklearn, TensorFlow, Keras, PyTorch, GBM, XGB, OpenCV, AutoML, CNN, Image Processing Statistic Tools: Statsmodels, A/B testing, PCA, Forecast and Trend Analysis, Regression and Clustering Analysis EMPLOYMENT HISTORY:

Senior Professional Application Designer

Gainwell Technologies for TennCare, Nashville, TN, USA (remote) (Jun 2022 - Oct 2023)

● Led a team as a Subject Matter Expert (SME) in the ETL migration project from ADF to Databricks based workflow, acted as a design architect in the execution of an automated workflow resulting in a 4x performance enhancement.

● Conducted training sessions for a team of four members and collaborated with cross-functional teams to develop requirements throughout the data modeling, design, and deployment phases.

● Ensured the implementation of robust security measures for data transfer using Azure services such as IAM, RBAC, and Key Vault. Conducted data validation processes to uphold quality and consistency checks throughout the entire Software Development Life Cycle (SDLC) and also performed unit and integration testing for the Databricks-based workflow.

● Compiled an extensive eligibility database for Medicare and Medicaid member data, with a focus on dually enrolled members, considering their eligibility criteria and effective dates.

● Implemented ML models to analyze fluctuations in member enrolment within Medicaid and Medicare subprograms and also built predictive models to find the reason behind member readmission in health homes based on the claims data.. Freelancer ML Specialist-Madras Medical College, India (remote) (Apr 2020 - May 2022)

● Collaborated with medical professionals to develop a robust ML model predicting feto-maternal outcomes, employing various preprocessing techniques to address skewed datasets.

● Generated data visualizations for physicians, facilitating the interpretation of raw Excel data. Effectively communicated the underlying narrative, assisting them in making informed decisions and selecting the appropriate research path.

● Implemented statistical models and ML models using statsmodel, H20 based AutoML and variants of decision trees, used optimization techniques like grid search for hyperparameter tuning enhanced the model accuracy. Junior Research Fellow-SSN College of Engineering, India (Apr 2019 - Mar 2020)

● Created a Delta Lake in Hadoop utilizing big data tools towards the project Immunization Coverage for Monitoring and Analysis: a project funded by Biotech Industry Research Council (BIRAC).

● Developed an infant fingerprint matching algorithm using CNN, and used improved performance techniques like transfer learning. Also converted raw images from edge devices to processed images using image processing and OpenCV. Internship Experience-Central Leather Research Institute, India (Oct 2018-Apr 2019)

● Built DL models using CNN and LSTM for classifying peptide sequences based on their specific functions. EDUCATION:

M. S in Computer Science and Engineering with concentration in Data Science Hindustan University, Chennai, India GPA 3.9 (Aug 2017 - Apr 2019) PhD(discontinued) Anna University, India (Jul 2019 - May 2022) Problem Statement: Improve accuracy through dynamic ML models for skewed data.