Jan 2024 – Present · 2 yrs 5 mos · Universe

• It's Unknown and I'm in the Doing.

Jul 2023 – Dec 2023 · 5 mos · Mumbai, Maharashtra, India · On-site

• As a Project Research Assistant at IIT Bombay in the field of artificial intelligence, I actively contributed to innovative AI research projects over a 6-month period. Collaborating with a dynamic team of researchers, I played a pivotal role in implementing and experimenting with advanced machine learning algorithms.
• During this tenure, I gained valuable insights into the project management domain, closely observing the work processes of Project Managers. This exposure provided me with a holistic understanding of project planning, execution, and delivery, enhancing my overall perspective on AI project lifecycles.
• My experience as a Project Research Assistant has fueled my interest in broadening my skill set beyond research. In the future, I aspire to transition into roles related to Project Management, Product Management, or even a Scrum Master. I am enthusiastic about applying my AI expertise in a more strategic and leadership-oriented capacity, ensuring successful project outcomes and contributing to the intersection of technology and effective project delivery.

Jun 2023 – Jul 2023 · 1 mo · Mumbai, Maharashtra, India · Remote

• As a Data Science intern at Oasis Infobyte Pvt. Ltd, I independently performed several responsibilities over the course of one month. Here is a summary of the tasks I covered during that period:
• 1. Dataset exploration and preprocessing: I worked with various datasets provided to me, thoroughly understanding their structure, variables, and potential challenges. Through exploratory data analysis (EDA), I gained insights, identified missing values, outliers, and inconsistencies. Additionally, I performed data cleaning, feature engineering, and normalization to prepare the datasets for model training.
• 2. Model selection and implementation: Considering the problem statement and dataset characteristics, I conducted extensive research to identify suitable machine learning (ML) and deep learning models. I implemented these models using Python and relevant libraries such as scikit-learn, TensorFlow, or PyTorch. To optimize model performance, I tuned hyperparameters using techniques like cross-validation and grid search.
• 3. Model training and evaluation: I trained the selected models on the prepared datasets. By splitting the data into training, validation, and testing sets, I ensured robust evaluation. Throughout the training process, I monitored the models' progress, assessed their performance using appropriate evaluation metrics, and iteratively improved their accuracy, precision, recall, or other relevant measures.
• 4. Documentation and reporting: Once the models demonstrated satisfactory results, I focused on documenting the entire process. I created comprehensive documentation that outlined the methodologies used, including preprocessing techniques, model selection, and hyperparameter tuning. Additionally, I prepared detailed reports summarizing the findings, performance metrics, and recommendations based on the models' results.

Dec 2022 – Jan 2023 · 1 mo · Mumbai Metropolitan Region · Remote

• As a Data Science Intern, I gained experience in the process of exploratory data analysis (EDA), which involved the following:
• 1. Collecting and importing data from various sources
• 2. Cleaning and wrangling data to ensure its accuracy and completeness
• 3. Visualizing data using tools such as Matplotlib and Seaborn to identify trends and patterns
• 4. Conducting statistical analyses to determine correlations and relationships between variables
• 5. Identifying and addressing outliers, missing values, and other anomalies in the data
• 6. Creating summary statistics and visualizations to present insights to the team.
• Throughout this process, I developed a strong understanding of the importance of EDA in uncovering hidden insights and patterns in data, and how it plays a critical role in the success of data-driven decision-making.

Mar 2022 – Sep 2022 · 6 mos · Mumbai, Maharashtra, India

• 1. Experienced a transformative 6-month Data Science Internship.
• 2. Gained exposure in Conversational AI, Machine Learning, EDA, Data Analytics, SQL, Statistics, and Python.
• 3. Developed chatbots using NLP techniques for Conversational AI projects.
• 4. Applied Machine Learning algorithms for classification, regression, and clustering tasks.
• 5. Conducted thorough EDA, cleaned and visualized diverse datasets.
• 6. Utilized SQL for data manipulation, querying, and database management.
• 7. Applied statistical techniques for hypothesis testing, regression analysis, and A/B testing.
• 8. Utilized Python and its libraries (NumPy, Pandas, Matplotlib, Scikit-learn) for data manipulation, analysis, and model development.
• 9. Equipped with a comprehensive skill set and ready to tackle real-world data challenges.

Jan 2021 – Oct 2021 · 9 mos · Mumbai, Maharashtra, India

• 1. For a remarkable three-month period, I had the privilege of being selected as a prestigious enterprise independent tester for none other than the world-renowned Bank of America's groundbreaking CARES initiative. My expertise and keen eye for detail were sought after to ensure the seamless functioning and utmost reliability of this innovative project.
• 2. My invaluable contributions to Bank of America's Centralized Operation Services (COS) hazard mortgage department as a Hazard Insurance Coordinator were nothing short of extraordinary. I played a pivotal role in safeguarding the bank's interests by meticulously coordinating and managing the intricate web of hazard insurance policies. My unwavering dedication and unwavering commitment to excellence helped maintain the highest standards of risk management within the department, making me an invaluable asset to the organization.

Jun 1999 – Present · 27 yrs · Duniya