I work at the intersection of data, AI, and business strategy, helping organizations move from raw data to actionable decisions. My focus is not just building models, but ensuring they deliver measurable operational impact, improve processes, and support business transformation initiatives.
I am a Data Scientist and AI Engineer with over 4 years of experience delivering AI and analytics solutions that directly impact business performance. My work spans across building data products, deploying machine learning systems, and enabling decision-making through scalable analytics. Rather than focusing purely on technical implementation, I prioritize aligning data solutions with business goals, whether it’s reducing operational inefficiencies, improving service reliability, or enabling real-time visibility into KPIs.
In my recent role at Allianz Technology, I developed AI-driven systems for SLA monitoring and forecasting that reduced service violations by 35% and significantly improved operational decision-making. I have also built end-to-end data pipelines, KPI dashboards, and RAG-based systems that reduced manual analysis efforts and enabled stakeholders to interact with data in a more intuitive way. Across roles at Innomotics and Cognizant, I consistently focused on translating complex data into clear business insights and automating processes to drive efficiency at scale.
What differentiates me is my ability to bridge the gap between technical teams and business stakeholders. I approach problems from a business-first perspective, identifying where data and AI can create tangible value, and then delivering solutions that are scalable, reliable, and aligned with organizational goals. I am particularly interested in roles that involve digital transformation, data-driven decision-making, and applying AI to solve real-world business challenges.