
After Ph.D., I transitioned from Cognitive Neuroscience to the industry. I developed a strong passion for Time Series forecasting and using Machine Learning.
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TS_forecasting_sales
November 26, 2024 – November 26, 2024
TS_forecasting_sales — GitHub repository
View ProjectDigital_Turbines_Auction_Bid_Price_Prediction
June 26, 2023 – June 26, 2023
Digital Turbine's Auction Bid Price Prediction!
View ProjectSales_forecasting_model
April 1, 2023 – April 1, 2023
The aim was to create and implement a predictive model that can forecast the number of items sold for a period of 8 weeks ahead.
View ProjectForecasted-Proportional_Index-new-measure-for-high-level-data-quality-assurance
October 23, 2022 – October 23, 2022
High-level information such as: number of panelists each day, can be used in order to identify outlier periods by using simple transformations and indexes. The project is a practical example of identifying outlier months based on number of participants for each day in order to assure the data quality.
View ProjectDoes-Engagement-at-Work-Prevent-Burnout-Statistical-approach
September 18, 2022 – September 18, 2022
The work is titled: "Does Engagement at Work Prevent Burnout?" and it was made as a part of dissertation project in Psychology Department.
View ProjectCustomer-retention
July 5, 2022 – July 5, 2022
The aim was to calculate retention index, understood as a engagement (in days) grouped by the type of the ad campaign, as well as to create a simple line plots.
View ProjectSodastream-vs-bottled-water-cost-prediction-ARIMA-model
July 5, 2022 – July 5, 2022
The aim was to predict how much money can be saved by using Sodastream as compared to bottled sparkling water, and how fast can investment be returned. The simple prediction was done using Autoregressive integrated moving average.
View ProjectCultural Fit Analysis
The candidate's projects are all personal and primarily use Jupyter Notebook, indicating a self-starter attitude. However, the lack of team projects or diverse technology exposure limits the assessment of cultural fit in a collaborative, production-oriented environment. The projects align with a Data Scientist role, but the breadth of tools and methodologies is narrow.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. No psychometric test results or interview feedback provided.