Alina Molnar

Clean, process and transform data in Python. Summary statistics with Pandas, Numpy. Visual data analysis with Seaborn and customization with Matplotlib. Build Machine Learning models in H2O with Distributed Random Forest and Gradient Boosting Machine. Predict numeric variable using categorical data as input. Score metrics on test set and deploy the approved models on unseen data. Report in CRISP-DM format. Present insights. https://github.com/alina-molnar/Beer-Recommendation-Project-Proof-of-Concept

Developed sterilization protocols. Increased embryo germination by 31% in Pelargonium and by 6% in Petunia wild seeds. Reduced infection rate by 66% prior to germination stage. Manage embryo rescue in Pelargonium, Poinsettia and Rose, in vitro germination in Petunia: design and implement experiment. Analyze results of growth media on Pelargonium and Petunia. Use insights to plan projects on other plants. Test the effect of light on plants in transparent containers with opaque covers for each growth media.

During University various traineeships and volunteering. Protocol search in scientific databases. Plan germplasm collection, monitor plant genetic resources, record data under FAO standards. Plant propagation. Sterilize and prelevate explants for tissue culture. Achievement: First documented collection of edible flowers in Romania.

Plan and manage tasks for a team of five and train new colleagues. Update monthly inventories, report sales and optimize stocks. Reduce by 30% the time needed to check stocks and invoices by increasing quantities and decreasing frequency of orders in fast selling goods.

Help and bill customers. Organize daily duties. Check incoming stocks.