I am a senior data science and analytics professional with expertise in machine learning, predictive analytics, credit risk, portfolio management, and financial modeling. I translate complex data into practical strategies that support growth, customer engagement, and risk-aware decision-making.
I currently lead analytics initiatives for global commercial card products, designing value propositions, evaluating card benefits, and developing customer targeting and marketing strategies. My work combines behavioral segmentation, macroeconomic research, cost-benefit analysis, and machine learning to improve retention, incremental spend, and product attractiveness.
My background includes consumer lending, commercial card products, credit and portfolio risk, CECL reserve methodologies, PD/LGD modeling, collections analytics, and early-warning indicators. I have developed scoring models, forecasting solutions, portfolio segmentation approaches, and macroeconomic dashboards to help organizations manage changing market conditions.
I work across the full analytics lifecycle, from requirements gathering and data preparation through model development, visualization, stakeholder communication, and executive presentations. I am experienced in Python, R, SQL, PySpark, Snowflake, Tableau, Power BI, AWS, and enterprise data environments.
I am an intuitive lifelong learner with a strategy-oriented mindset and a strong foundation in mathematics and statistics. I am passionate about responsible machine learning, time-series forecasting, advanced visualization, and using data to quantify uncertainty and drive sustainable business growth.
