Hi, I am
Software Engineer, AI & ML
With over 9 years of experience as a Software Engineer complemented by 4 years of hands-on learning and application in Data Science and Machine Learning, I bring a unique blend of software development expertise and a strong foundation in data-driven decision-making.
I excel in frontend technologies such as ReactJS and have strong skills in backend development with Python, Node.js, FastAPI, MySQL, and DynamoDB. Furthermore, I have experience in creating and deploying scalable serverless applications on AWS using AWS Lambda and AWS Cloud Development Kit.
My growing expertise in Machine Learning and Data Science includes working on personal projects in predictive modeling, data analysis, and ML-driven applications. I am currently enrolled in the Scaler Data Science and Machine Learning Program to deepen my expertise in ML algorithms, statistical modeling, and AI-driven solutions.
I am actively seeking opportunities where I can apply my expertise in ML and Data Science to drive impactful, scalable solutions while bridging the gap between software engineering and AI-driven innovation. If you're looking for a versatile engineer with a strong product mindset, a passion for machine learning, and a proven track record in delivering effective AI-driven solutions, let's connect!
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This app uses Gen AI to evaluate and rank candidates based on how well their CVs match a given job description, helping recruiters streamline the candidate selection process.
This application predicts the driver churn rate for a ride-sharing company using machine learning algorithms.
This system scans daily market data to generate trade signals, automatically places orders, and saves trade data to a database.
Was a member of the core team that developed Grassdoor, an e-commerce website and its associated admin portal using ReactJS.
Led the company's transition to data-driven decision-making through ML implementation.
Communicated with stakeholders to gather requirements and provided recommendations that considered both business and technical viability, resulting in reduced development time.
Built an ML model using the Random Forest algorithm to predict monthly sales resulting in a 15% increase in profit and better inventory planning.
Built a recommender system using the Apriori algorithm resulting in increased sales across product categories.
Developed sales analytics dashboards by constructing efficient SQL queries to aggregate data from various sources
Increased the engineering team's efficiency by recruiting, training, and supervising a group of 7 junior developers.
Developed cost-effective serverless microservices using AWS CDK, AWS Lambda, DynamoDB, and API Gateway.