A
Anjali Ladwa
About
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Karnataka, India
Résumé
Jobs
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Data ScientistAdaAug 2023 - Current (3 years 3 months)• Developed three key Power BI dashboards for a BFSI client (Aeon Credit Service Malaysia): Customer 360 Dashboard, Campaign Performance Report, Customer Base Analysis enabling the client to make data-driven decisions. • Built Python-based automated workflows using DigDag for routine data processing, saving ~20 hours of manual effort weekly. • Developed a churn prediction model using logistic regression and performed extensive EDA on large financial datasets to predict user behavior. • Designed and implemented A/B experiments on financial products to assess performance and reduce customer churn by ~3%. • Built an RFM segmentation model for the client's card products to support personalized targeting and campaign optimization. • Design- QMachine Learning EngineerQuantiphi,Aug 2022 - May 2023 (10 months)• Performed exploratory data analysis (EDA) on large medical industry datasets using Python libraries such as Pandas, NumPy, and Scikit-learn, identifying key patterns to support the development of a classification model. • Utilized data visualization libraries, including Matplotlib and Seaborn, to effectively present insights and trends. • Explored and leveraged Google Cloud Platform services, including Vertex AI AutoML, Workbench, and Pipelines, to deliver scalable machine learning solutions.
Education
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- Bachelor's degree inAcharya Institute of TechnologyAug 2018 - Aug 2022 (4 years 1 month)
Projects (professional or personal)
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- CChurn Prediction ModelJun 2024 - Dec 2024 (7 months)• Developed a churn prediction model for a credit service provider using logistic regression on, achieving 92% accuracy, an AUC of 0.84, and a recall of 0.72. The model effectively reduced customer churn by ~3%, enabling proactive retention strategies. Extensive Exploratory Data Analysis (EDA) was conducted to identify key features influencing churn. • Tech stack: Python, SQL, Data Analysis
- Campaign Performance ReportAdaDec 2023 - Mar 2024 (4 months)• Built out the data and reporting infrastructure from the ground up using Power BI and SQL to provide real-time insights into the product, marketing funnels, and business KPIs saving ~90 hours of monthly labor. • Tech Stack: SQL, Power BI.