- Overseeing all aspects of company operations and leading the development of innovative data science solutions.- Using data-driven insights to drive growth and improve operations- Working closely with a talented team of data scientists to develop cutting-edge solutions.- Responsible for managing budgets, overseeing personnel, and collaborating with other departments to align data science solutions with overall company strategy.- Working with stakeholders across the organization to drive growth and achieve company goals.

- Work on Alternative Data to figure out Actionable Insights- Use Statistical and Machine Learning Approaches to Discover Useful Insights- Identify abnormality in the data using unsupervised ML Algorithms- Work On Data Science Architecture PipeLines to Maintain Data- Work On Data Visualization for Presenting Insights and identifying abnormal data records.- Created an Automated Library that helps to wrangle the data using a few lines of codes.- Created an Automated NLP Library that identifies the similarities between the data and removes the Duplicated Data- Handle the BIg Data (approx more than 20 Million Data) considering using the Optimized Algorithms, considering the constraints of Memory and Time ComplexityLanguages: Python, SQL Database / Data Warehouse: MySql, Postgres, Snowflake Libraries: Pandas, Numpy, sklearn, Keras, NLTK, spacy, strsimpy, fuzzy

- An Open Source Library that helps data scientist to explain their Machine learning Models using state of art interpret Machine learning techniques.- Startup Affiliated With New York University (NYU)- Researching On Explainable AI techniques- Working on a Scalable and Distributed Library that interpret Models using Advance and Sophisticated Techniques such as Global / Local Explanations, Summary Plot, etc - Working on Visualization Techniques that help to translate the insights from the Machine learning Models- Working on Real-Time Monitoring of Machine Learning ModelsLanguage: PythonLibraries : Plotly- Dash,Pandas ,Numpy, Scikit-Learn,H2o,SHAP,Catboost,XbgoostResearch Area: Local /Global Explanations, Distributions about the Data, Cohort Analysis and Ranking Similar Profiles within the data

- Created Data Science Course - Trained Fresh graduates for Data Science Roles- Live Coding Sessions

- Worked on Alternative data related to Rural and Urban communities to identify problems in marginalized communities- Worked as a Volunteer in the PWG- Worked on World Bank data to figure out the marginalized communities- Used Statistical and Visualizing techniques to list down the problems in the region or communityLanguage: Python Libraries: Pandas, Numpy, Matplotlib, Seaborn, PlotlyVisualization Tools: Tableau, PowerBI

- An Auto ML platform that empowers businesses with affordable AI solutions.- Startup Affiliated With New York University (NYU)- We Failed to attract the audience - Developed Virtual Data Scientist- An End to End Machine Learning Platform from Data Wrangling to Model Building and Deployment by few clicks- Worked on Distributed and Scalable Data Cleaning Library that wrangles the data automatically using Sophisticated Machine and Deep Learning Algorithms- Worked on Auto ML library that helped in identifying the best model and its hyperparameters based on the accuracy- Worked on Data Pipelines and Model Deployment Using AWS servicesLanguages: PythonLibraries: Pandas, Numpy, Scikit-Learn, KerasDistributed System Libraries: PySpark, Dask Cloud Platform: AWS services

- Started as an intern then promoted as Junior Developer- Worked on chatting applicationLanguage: Html /CSS ,javascript.Node.jsDatabase: MysSQL, NoSQl, Redis