Suyash Mali

With a strong academic background in Applied Data Science and Analytics, and a Bachelor’s in Electronics and Telecommunication, I’ve always been drawn to the intersection of technology and impactful problem-solving. Currently pursuing my Master’s at SRH Hochschule Heidelberg, I bring a blend of technical depth and curiosity to everything I work on, whether it's time series forecasting, generative AI, or building real-time data pipelines. Over the past few years, I’ve applied my skills across diverse industries including retail, e-commerce, and transportation. At Paretos, I designed a demand forecasting system that combined weather and sales data to improve stock management by 50%. During my time at Larsen & Toubro, I built full-stack analytics tools to visualize railway operational data, automating reporting workflows and enhancing data delivery at scale. From developing candidate-job matching systems using ML to deploying scalable infrastructure using Docker and Hadoop, I’ve thrived in roles that demand both innovation and execution. What truly sets me apart is my ability to quickly adapt, self-learn, and dive deep into new domains. I’m passionate about using data science to power tech-driven innovations and turn raw data into strategic insights that matter. I enjoy collaborating with cross-functional teams, simplifying complex insights for non-technical stakeholders, and building solutions that align with business goals. As I move forward, I’m seeking opportunities that challenge me, allow me to build meaningful products, and create measurable impact, especially in the fields of digital health, sustainability, or AI-driven platforms. I’m excited to keep learning, building, and collaborating on impactful solutions.