Dhruvi Makadia
Princeton,TX
Summary
Passionate AI Engineer with over 6 years of hands-on experience specializing in machine learning, deep learning, and natural language processing. Proven track record of conceiving and implementing innovative AI solutions by harnessing cutting-edge technologies. Adept at collaborating with cross-functional teams to define project objectives and deliver high-impact solutions. Adapt at engaging with stakeholders, providing timely insights, and ensuring regulatory compliance. Proficient in a wide range of tools and technologies, Python,machine learning,ensemble modeling, algorithm development, supervised/unsupervised learning, data cleaning, data integration,model optimization, anomaly detection, data analytics/visualizations, business strategy and analytics.
Overview
7
7
years of professional experience
1
1
Certification
Work History
Data Scientist
Comcast
03.2022 - Current
- Developed and implemented a customer churn prediction model, resulting in a visible reduction in churn rate and collaborated with cross-functional teams including marketing, customer service, and product development to leverage insights from the churn prediction model.
- Utilized machine learning techniques such as logistic regression, random forests, and gradient boosting to build predictive models.
- Developed and implemented generative AI models, using Python, machine learning, NLP, and deep learning techniques, including GPT, VAE, and GANs.
- Collaborated with cross-functional teams for optimizing LLMs for enhanced performance in web applications through effective prompt engineering and model evaluation to align AI initiatives with business objectives.
- Familiarity with LLM's and optimizing them for specific use case prompt engineering, RAG, fine tuning, etc.
- Created clear and concise documentation, including technical specifications, user guides, and presentations, to communicate complex AI concepts to both technical and non-technical stakeholders.
Data Scientist
Milbank LLP
02.2021 - 02.2022
- Implemented data preprocessing techniques to clean and normalize legal text data, ensuring the accuracy and reliability of NLP models.
- Understanding of fine-tuning NLP models, including transformer-based models such as BERT and GPT, for various language understanding tasks including language generation, sentiment analysis, and entity recognition.
- Familiarity with NLP libraries and frameworks such as NLTK, spaCy, and Transformers.
- Developed interactive dashboards and reports using Tableau and Power BI to visualize complex datasets and provide actionable insights to stakeholders.
Junior Data Scientist
Teleysia Networks PvtLtd
05.2017 - 01.2021
- Performed exploratory data analysis to uncover uncover trends, patterns, and outliers, informing data-driven strategies and initiatives.
- Worked on a team to analyze and visualize data using Python libraries such as NumPy, Pandas, and Matplotlib.
- Assisted in the design and implementation of data pipelines and workflows for data collection, cleaning, and preprocessing and presented findings and recommendations to team members and stakeholders through written reports and presentations.
- Collaborated with software engineers to deploy machine learning models into production environments, ensuring seamless integration with existing systems.
- Presented findings and recommendations to management using visually appealing dashboards and reports created in Excel, effectively communicating complex technical concepts to non-technical stakeholders.
Education
Master of Science - Data Science
New Jersey Institute of Technology
Newark, NJBachelor of Science - Information Communication Technology
New L.J Institute of Technology
Gujarat, IndiaSkills
- Operating Systems: Windows, MacOS
- Programming and Technical Skills: Python, R programming, SQL, Databricks, PySpark, Prediction, Storytelling, Creating Proof of concepts
- Deep Learning : Neural Networks,CNN,ANN,Scikit learn,TensorFlow,PyTorch, Keras, GANs, GPT, Spark ML, Data Visualization, Descriptive Analytics, Predictive modeling, Prescriptive Analytics, Risk
- Machine Learning: Modelling,Regression, classification,Clustering, Decision trees,Ensemble methods, Random Forest, KNN, SVM, Randomforest, XGboost, PCA,K- Means,Neural Networks, Outlier detection, Anomaly Detection, Hypothesis Testing, Data cleaning, Data Preprocessing, Dimensionality reduction, recommendation system, Reinforcement Learning
- NLP: Transformers, BERT, NLTK,Bag of Words, textclassification, named entity recognition, topic modelling
- Visualization: Power BI, Tableau,Python,Matplotlib,
- Other: Hadoop ecosystem, AWS services (EC2, S3), Azure ML,Github, Docker, ML Flow, Azure ML studio
Certification
Microsoft Certified: Azure AI Fundamentals Issued by Microsoft | July 2023 |Skills Covered: Introduction to AI, Azure AI services, natural language processing, computer vision, machine learning, conversational AI.
Microsoft Certified: Azure AI Engineer Associate Issued by Microsoft | July 2023 |Skills Covered: Implementing machine learning models, natural language processing, computer vision, deploying AI solutions on Microsoft Azure.
Microsoft Certified: Azure Data Scientist Associate Issued by Microsoft | Oct 2023 |Skills Covered: Machine learning model development and deployment on Azure, as well as proficiency in data preparation, visualization, and ethical data handling.
Academic Projects
- Breast Cancer Prediction using Machine Learning: Develop a machine learning model to predict breast cancer images.Evaluated on features extracted from medical images.Evaluate the model's performance using metrics such as accuracy, precision, recall, F1-score, and ROC-AUC. Goal was to achieve precission should be as high as possible. Technologies: Python (scikit-learn, pandas, numpy), data visualization libraries (matplotlib, seaborn)
- Predictive Analytics for E-commerce: Develop a predictive model to forecast customer purchase behavior in an e-commerce platform. Apply machine learning algorithms (e.g., regression, time series) to predict future purchase patterns.Evaluate model performance using appropriate metrics (e.g., RMSE, MAE). Technologies: Pandas, scikit-learn, Jupyter Notebook, data visualization libraries.
Timeline
Data Scientist
Comcast
03.2022 - Current
Data Scientist
Milbank LLP
02.2021 - 02.2022
Junior Data Scientist
Teleysia Networks PvtLtd
05.2017 - 01.2021
Master of Science - Data Science
New Jersey Institute of Technology
Bachelor of Science - Information Communication Technology
New L.J Institute of Technology