Mesyella . Email & Phone Number

Indonesia

As an Associate Data Scientist specializing in marketing campaign analytics, I played a role on driving data-driven insights and optimizing strategies to enhance marketing performance. Here are some highlights of my contributions:- Voucher Propensity Modeling: Developed models to identify customer with the highest propensity to redeem vouchers, resulting in targeted promotional campaigns and increased redemption rates.- Recurring Purchase Model: Developed a recurring purchase model to predict customer subscription behavior, incorporating time-series regression. By accurately forecasting subscription renewals, this model enabled proactive retention strategies, reducing churn rates and increasing customer lifetime value.- Persona: Help the development and refinement of customer personas through extensive analysis of demographic, behavioral, and transactional data, enabling more personalized and effective marketing communication strategies tailored to specific audience segments.- Ads Restriction Model: Conducted in-depth analysis of advertising restrictions, utilizing some predictive models and OCR techniques to identify products that are not supposed to be in advertisement.In addition to project-based initiatives, I also contributed to:- Data-driven Decision Making: Leveraged statistical analysis and machine learning algorithms to extract actionable insights from large datasets, informing strategic decisions and driving continuous improvement in campaign performance.- Cross-functional Collaboration: Collaborated closely with marketing and campaign teams to align data-driven initiatives with business objectives, fostering synergy and ensuring the effective implementation of analytical insights across the organization.Through these endeavors, I played a key role in driving measurable results, optimizing marketing strategies, and delivering tangible value to the organization.

As a Data Science Intern, I engaged in impactful projects aimed at leveraging data-driven insights to drive strategic decision-making and enhance business outcomes. Here are some highlights of my contributions:- Node Pool Estimation: Develop a predictive models to estimate node pool requirements, utilizing historical data and machine learning techniques to forecast resource demand accurately. This initiative optimized resource allocation and minimized operational costs.- Customer Affinity Analysis: Develop a model to identify patterns of affinity between categories of product and customer.- Customer Propensity Modeling: Designed and implemented models to assess customer propensity for specific actions, such as purchasing a specific category of product.In addition to project-based contributions, I actively participated in:- Conducted exploratory data analysis to understand and gain insights of the data- Utilized Python and SQL to manipulate, clean, and preprocess data- Developed machine learning models, including regression, classificaiton, and clustering to improve operational efficiency and drive business growth- Utilized data visualization tools like Google Data Studio to create dashboards and reportsThrough these experiences, I honed my analytical skills, gained practical experience in machine learning and data analysis techniques, and contributed to driving tangible business outcomes through data-driven decision-making.

Indonesia

Indonesia

Indonesia

Indonesia

Indonesia

Indonesia

Indonesia

Indonesia