Data Scientist Machine Learning

Javeria Dinar

************@*****.*** +1-551-***-**** https://www.linkedin.com/in/javeriadinar/ https://github.com/joedinar EDUCATION

Stevens Institute of Technology, School of Business, Hoboken, NJ Master of Science in Business Intelligence & Analytics GPA: 3.92/4.0 May 2025 Academic Award: Master’s Provost Fellowship

Karakoram International University, Gilgit, Pakistan Master of Philosophy (MPhil) in Mathematics GPA: 3.85/4.0 (Gold Medalist) July 2022 Academic Award: Scotland Pakistan Scholarship for Young Women and Girls, Master’s/MPhil Institute of Business Administration, Karachi, Pakistan Bachelor of Science in Economics & Mathematics GPA: 3.52/4.0 August 2016 Academic Award: Global Undergraduate Cultural Exchange Program to study one semester in the USA SKILLS

Software & Tools: SQL, Python, R, Microsoft Suite (Excel, Word, PowerPoint), Tableau, Power BI, SAS, Alteryx, STATA, Latex

Technical Skills: Exploratory Data Analysis, Data Visualization, Statistical Analysis, Financial Modelling and Analysis, Machine Learning Modelling, Times Series Forecasting Soft Skills: Willingness to learn, Commitment, Communication skills, Meeting deadlines, Resourcefulness, Problem Solving EXPERIENCE

GLOW Consultants (PVT) Limited Islamabad, Pakistan Data Analyst January 2018 – June 2023

• Streamlined workflows by 20% using Power BI/Tableau dashboards built on 500K+ records, enabling faster, data- driven decisions

• Cut project execution time by 15% by identifying delays and resource gaps through SQL and Python analysis

• Evaluated program impact by coding insights from 10+ focus groups and 30+ interviews into actionable metrics

• Uncovered cost inefficiencies via trend and variance analysis, reducing project overhead by 10%

• Delivered insights through concise reports and dashboards, highlighting KPIs and gaps, boosting stakeholder satisfaction by 30%

Center for Economic Research in Pakistan (CERP) Lahore, Pakistan Field Researcher September 2017 – December 2017

• Assessed workplace satisfaction and staff development needs by conducting surveys with 250+ teaching and non- teaching staff of Beaconhouse schools

• Identified key areas for improvement by analyzing survey data using R and Stata, providing recommendations on resource allocation and staff performance enhancement ACADEMIC PROJECTS

Detecting Fraud in Health Insurance Claims Using Predictive Modeling March 2025 – May 2025

• Built predictive models (Random Forest, XGBoost, ensemble learning) to detect fraud in health claims with 91% accuracy

• Conducted extensive analysis on structured claims data, uncovering fraud hotspots by provider, region, and procedure

• Designed interactive Tableau dashboards to visualize fraud risk hotspots by provider, procedure type, and region, enabling proactive investigative prioritization and operational scalability for insurance fraud teams Lie Detection Using Micro-expressions with CNN and LSTM Networks March 2025 – May 2025

• Developed a hybrid CNN-LSTM model using TensorFlow to detect deception from facial micro-expressions, achieving 92% training accuracy on the CASME dataset

• Automated preprocessing pipelines for frame extraction and emotion labeling, enhancing model training efficiency for micro-expression based lie detection

Strategic Revitalization for Injectable Anesthesia Drug September 2024 – December 2024

• Conducted a comprehensive market cannibalization analysis using Medicare claims data on injectable anesthesia products (Ketorolac, Midazolam, Fentanyl, Propofol)

• Identified key competitive drivers and proposed data-driven strategies (targeted territory interventions, co-pay assistance, and brand repositioning) increasing market share by 7% and reducing market share loss by 20% within the analyzed period