Bots Development:Design and develop bots that imitate human behavior to automate the collection of data forApplication-to-Person (A2P) messaging models.Implemented and trained Random Forest models for live detection, KNN, ensuring accurateand real-time analysis of the collected data. Optimized the models for performance andscalability.Develop and implement OCR systems to detect and locate words on Android devicescreenshots. Extract and utilize button coordinates for automating device interactions via ADBcommands.Design and deploy a bot that connects to the Telegram API to automate the sending ofcampaign messages. Integrate OCR to navigate and interact with the Android interfaceaccurately.Optimize the bot algorithms to operate efficiently and avoid detection by app defenses,ensuring the successful execution of tasks.Simbox/Spam Detection:Big Data Aggregation and Processing: Utilized PySpark and Dask to process large-scale Call Detail Records (CDRs), enabling efficient data aggregation and analysis.Pattern Recognition: Developed advanced algorithms, including Support Vector Machines (SVM), to identify patterns indicative of simbox usage, fraudulent activities, and spamming, significantly enhancing detection accuracy.Fraud Detection: Implemented data-driven methods to monitor and detect fraudulent activity in real-time, leveraging big data technologies to ensure scalability and robustness.Spam Detection: Applied machine learning techniques to analyze communication patterns, leading to the successful identification and mitigation of spam across networks.

Software Development and Maintenance:Assist in the development of software applications using C# and Python.Write, test, and maintain code to ensure it meets quality standards and performs effectively.Participate in integrating software components and third-party libraries.Identify and resolve bugs and issues in existing code.Perform unit testing and support integration testing to ensure functionality and performance.Documentation and Continuous Improvement:Document code, processes, and system designs clearly and accurately.Maintain up-to-date records of development work and changes.

Design and Development:Design, develop and maintenance of high-performance C++ and Python applications.Develop and optimize algorithms and data structures to meet high-performance andscalability requirements.Collaborate with cross-functional teams to understand requirements and translate theminto technical specifications.Define success criteria such as execution speed, accuracy, and latency requirements.Ensure the system complies with regulatory requirements and trading rules.Clearly define the trading strategy you want to automate (e.g., trend following, meanreversion, arbitrage).Choose technical indicators and signals that your strategy will use (e.g., moving averages,RSI, MACD).Code Quality and Testing:Write clean, maintainable, and efficient code, adhering to industry best practices and codingstandards.Implement and conduct comprehensive unit testing and integration testing to ensuresoftware reliability and robustness.Perform code reviews and provide constructive feedback to team members.Monitor project progress and address any technical issues or roadblocks.

International Paints Fair is a comprehensive hub store for construction needs, offering an extensive selection of materials and tools.Catering to both professional builders and DIY enthusiasts, its expert staff is always ready to guide customers towards the perfect products for their projects.My Data Scientist Responsibilities at IPF includes:• Data Science Integration and Digitalization: Integrated data science into the business by digitalizing stock and daily sales data. Implemented algorithms on Python using libraries such as Pandas, NumPy, Scikit-learn, and PyTorch. Utilized SQL for data manipulation, analysis, and querying.Integrated data from disparate sources to provide a comprehensive view of business operations.• Machine Learning and Data Preprocessing: Worked with Python to preprocess data, extracting relevant features for machine learning algorithms.Developed models to determine the optimal number of items to add to the daily stock. Used clustering techniques to identify products frequently purchased together, enabling targeted marketing and inventory management strategies.• Business Insights and Analysis: Utilized analytical and technical expertise to provide actionable insights and proposals for business improvements.Actively engaged in analyzing multiple models to address specific business challenges and drive informed decision-making.Contributed to enhancing both company operations and customer experience by up to 30%.

Subject: “Fake news detection, using Machine Learning and Deep Learning”• Worked on multiple and large datasets containing tweets from Twitter and news from other platforms • Implemented algorithms in Python using Pandas, NumPy and scikit-learn to create a file of the features used in the process. I extracted 5 features: Sentiment of each tweet which is a number between -1 and 1, Text length, Average word length, Adjective count and Word count.• Trained and tested machine learning algorithms like Support Vector Machines (SVM), Naïve Bayes and K-nearest neighbors(KNN). Naïve Bayes got a precision score of 96% and KNN got a precision score of 80%• Trained and tested a deep learning algorithm called Long-short term memory(LSTM) and got a precision score of 99.8%