Where Passion
Meets Will
Artificial Intelligence Solutions Architect • Experienced Machine Learning Researcher • Woman in AI • Educator • Developer
Discover my personal portfolio, a tapestry of silent achievements that embody growth and transformation. From pioneering research to transformative projects, join me in celebrating these pivotal moments. Explore and be inspired to embrace your own achievements and the endless potential of ongoing learning.
Fueling Success
Dive into some of the companies and organizations I collaborated with.
Where Data meets Science
Dive into some of my professional projects
Project 1
Next-Gen Data Integration
Data Solution in Cloud Integration & ETL Architecture for Cloud Cost Computing Product for Silicon Valley Start-Up
Role: Senior Data Scientist
Company: Arcurve
Client: Sillicon Valley Start-Up
Duration: 7 Months
Responsibilities: Overseeing Entire Data Domain, Data Identification and Acquisition, Data Engineering and Integration, ETL Architecture and Optimization, Load Testing and Data Storage, Data Processing and Analysis, Active Collaboration and Stakeholder Management, Presentations
Key Areas: Data Engineering, Cloud Computing & Integration, CI/CD, Advanced Analytics, ETL, Architecture & Design
Project 2
Harnessing Generative AI for Search Engine
Harnessing GenerativeAI for SciVal to Revolutionizing Research Analytics: Unveiling Patent Analytics through Large Language Models (LLMs) BERT Integration in SciVal
Role: Data Scientist III
Company: RELX
Client: LexisNexis, SciVal
Duration: 10 Months
Responsibilities: R&D, Data Evaluation and Analysis, Model Selection (NLP and LLMs), Model Testing and Evaluation, Model Selection and Implementation, Collaboration and Stakeholder Management, Client Communication and Stakeholder Engagement
Key Areas: Generative AI, LLMs, Transformers, BERT, Text Classification, NLP, Search Engines, Research & Patent Analytics
Project 3
Enhancing Funding Recommender System
Creating Eligibility Features for Data-Driven Funding Recommender System: Amplifying Researcher Funding Experiences through Advanced Analytics
Role: Data Scientist III
Company: RELX
Client: Funding Institutional
Duration: 6 Months
Responsibilities: R&D, Data Quality Analysis, Feature Design & Architecture, Feature Testing & Selection, Implementation & Production, Monitoring & Client Feedback, Collaboration & Stakeholder Management, Presentations
Key Areas: Advanced Analytics, Recommender Systems, Research Products
Project 4
NLP-ML infused Recommender Algorithm
Harnessing the Power of NLP and Machine Learning: Scalable, Hybrid Recommender System called LDA-LFM (Latent Dirichlet Allocation – Latent Factor Models) leveraging textual reviews, ratings and user demographics for enhanced article recommendations through advanced information retrieval
Role: Researcher
Organization: Erasmus University Rotterdam
Duration: 7 Months
Responsibilities: R&D, Data Collection, Model Development, Training, Evaluation and Optimization, Collaboration with Co-Author (Professor of Computer Science), Scientific Writing, Presentation
Key Areas: Information Retrieval, NLP, Topic Modelling, LDA, Matrix Factorization (LFM), Recommender Systems, Machine Learning, AI, Research
Project 5
System Failure Detection With AI
Outlier Detection in Time Series: Detecting Gas Station System Failures using Artificial Intelligence, Deep Learning (Autoencoders with LSTMs) and Statistical Modelling
Role: Senior Data Scientist
Company: Arcurve
Client: 7Eleven
Duration: 1 Month
Responsibilities: R&D, Data Collection, Model Development, Model Training and Evaluation, Technical Documentation, Collaboration & Stakeholder Management
Key Areas: Time Series Analysis, AI, Deep Learning, Autoencoders, LSTMs, Outlier Detection, Statistical Modelling
Project 6
ML Re-ranker for Recommender System
Harnessing Machine Learning, (XGBoost) and A/B Testing for Building a Re-ranking Model to Enhance Mendeley Suggest Recommender Algorithm
Role: Data Scientist I
Company: Elsevier
Client: Mendeley Suggest, Science Direct
Duration: 6 Months
Responsibilities: R&D, Model Evaluation, Data Collection, Feature Engineering, Model Development, Model Testing and Evaluation, Experimentation with A/B Testing, Presentations
Key Areas: Machine Learning, A/B Testing, Recommender Systems, Research Products
Project 7
Data-driven Marketing with Machine Learning
Harnessing Machine Learning for Customer Segmentation and Retention: Crafting a Data-Driven Loyalty Card and Targeted Marketing Strategy Through Group Dynamics Prediction for the Largest Liquor Store in the Netherlands
Role: Data Science Intern
Company: NewCraft & Erasmus University
Client: Gall&Gall
Duration: 5 Months
Responsibilities: R&D, Data Collection, Model Selection, Model Development, Model Training and Evaluation, Technical Documentation, Collaboration & Stakeholder Management, Presentations
Key Areas: Machine Learning, Clustering, K-Means, RFM-Segmentations, Dimensionality Reduction, PCA, Decision Trees
Project 8
GeoAnalytics with Machine Learning
Harnessing Machine Learning and Advanced Analytics (Causal Analysis) for Decoding Landslide Climate Triggers and using ML (DBSCAN clustering) to detect Landslide Hotspots
Role: Senior Data Scientist
Company: Arcurve
Client: WSP Golder Environmental Consulting
Duration: 2 weeks
Responsibilities: R&D, Data Evaluation & Integration, Feature Engineering, Model Development, Training, Evaluation and Optimization, Collaboration & Stakeholder Management, Client Reporting, Presentations
Key Areas: Causal Analysis, Correlation Analysis, Machine Learning, Clustering, Feature Engineering
Data Science and AI Handbook
Handbook to learn everything about Data Science and AI, and how to land a job in the field
Self-Led Learning
Dive into some of my self-directed and self-motivated personal projects, Case Studies
Predicting Stock Prices with RNNs
Case Study 1
Key Areas: AI, Deep Learning, Time Series, Recurrent Neural Networks, LSTMs, Stock Price Prediction
Image Recognition with CNNs
Case Study 2
Key Areas: AI, Deep Learning, Image Recognition, Convolutional Neural Networks, Computer Vision
Predicting Customer Churn with ANNs
Case Study 3
Key Areas: AI, Deep Learning, Churn Rate Prediction, Artificial Neural Networks
Playlist Success with ML
Case Study 4
Key Areas: Product Data Science, Causal Analysis, Linear Regression, Machine Learning, Music Playlist
More Case Studies
Here are Some More Case Studies I Worked on in the Past
Missing Data Imputation with Advanced Statistics
Using Single and Multiple Imputation Stats Models to Impute Missing Data
Anomaly Detection with ML (Isolation Forest)
Using Unsupervised Machine Learning To Detect Fraudulent Activity in Transactions
Robust Classification with Advanced Statistics-FastMCD
Making Linear Discriminant Analysis (LDA) Robust with FastMCD