Wolt

Senior Data Scientist

Meta

Area of Responsibility: Cross-functional, product data science in Remote Presence Org. Responsible for identifying user needs and building new features in video calls on the Family of Apps. Support, design, and analysis of product A/B experiments.

Unfortunately, my role was impacted by the Meta massive layoffs in November 2022. This layoff happened a month before even completing my probationary period and was not performance based. During my short time at Meta as a Senior Data Scientist, I have learned a lot and connected with some truly amazing people.

trivago

Area of Responsibility: Empower the Bidding Models team to develop models and algorithms, run analyses and achieve our business goals by providing guidance and setting best practices. Challenge the status quo, propose ideas and give guidance for the algorithm development. Empower team members and support their professional development.

Data Science Team Lead - Bidding models

Area of Responsibility: Data Scientist - Auction Domain. Continuously improve the Automated Bidding algorithms with state-of-the-art statistical models. Increase the product's value by incorporating new features in the models. Optimise the algorithm data pipelines by using latest technologies to ensure stability, scalability and efficiency.

Data Scientist

Faculty of Mathematics, University of Belgrade

Working on a numerical codes targeting high velocity flows in astrophysical fluid dynamics, which uses a distributed infrastructure (OpenMPI). Modelling the radio evolution of supernova remnants by using hydrodynamic simulations and and non-linear particle acceleration.

Research Assistant, Faculty of Mathematics

Estimating distances of supernova remnants: sample selection, Monte Carlo simulations and robust analysis with non-standard regressions.

Junior Researcher

Solid knowledge in statistics and machine learning supported by more than 6-year experience in solving complex scientific problems, exploring, modelling and interpreting data. Experience in optimising the algorithm data pipelines by using latest technologies to ensure stability, scalability and efficiency. Passionate about researching, technology, taking on challenges and solving new kinds of problems.

"All models are wrong, but some models are useful."
George Box

Ako znate neke mlade, srednjoškolce, koji su zainteresovani za podatke, statistiku, data science, mašinsko učenje, prenesite im da postoji ovaj letnji naučni kamp i ohrabrite ih da se prijave. ✨ 

Rok za prijavljivanje je do kraja marta (još 10-ak dana), a sve detalje možete videti na linku: https://lnkd.in/d4aNh6s2 

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