Mining precious patterns in strategic commodities for financial and maritime actors

4seee drills for signals across a wide range of data reservoirs to anticipate where the price of crude oil is heading. The latest Machine Learning technologies and time series analysis frameworks are infused with expert domain knowledge and human experience. The result: a new kind of augmented financial intelligence. By understanding markets as complex living systems we detect recurring phenomena in deep data.

To steer your ship at night, understand the stars. To steer your ship today, understand data.

Price fluctuations in Brent and WTI evoke premiums and discounts in the daily pricing of refined products such as marine gasoil. From one day to another, refueling a vessel can turn from a bargain into a losing trade. Our solution: a prediction engine fueled by real-time data mining that is built to pinpoint the optimum time window for transactions in oil spot markets worldwide.

Preparing ship owners for the 2020 market disruption in marine fuels

Come 2020, new sulfur-cap regulations will be in place upending the current bunker market. Our model-based procurement strategies allow shipping companies, refineries and other stakeholders to look beyond the horizon of uncertainty. Gathering specialists from data science, quantitative finance, Operations Research and the natural sciences, we harness advanced statistics for actionable price forecasting and proactive decision-making.



Alexander Raguz


Alexander joined 4seee in 2018 as Chief Investment Officer providing market guidance and expertise for the machine learning team. In 2020 he took over the role as CEO leading the company in its delivery of the only platform for predicting the optimal time for fuel oil purchase decisions. As CEO, Alexander heads up all aspects of the company’s strategy, product, operations and go-to-market functions.

Previously he worked as an option market maker and proprietary trader for one of Europe’s biggest energy trading firms. He is also a partner in a private investment group focusing on long term absolute return strategies.

In his free time, Alexander enjoys time with his family and friends.


Ekaterina Kramarenko

Lead Data Scientist

Ekaterina graduated with distinction from Saint-Petersburg State University with a Master’s degree in Applied Mathematics and Control Processes. Previously, she worked for 8 years at a trading software and services provider, gaining experience in quantitative finance.

Ekaterina is Lead Data Scientist at 4seee. She is the architect of the automated prediction engine, maintains the distributed computing infrastructure and supervises model production from start to finish.

In her free time Ekaterina is open to learning something new everyday, travelling the world, oil painting and trading stocks on her own as a hobby.

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Ekaterina Lopatina

Data Scientist

Ekaterina started work in 4seee as a freelance Data Scientist in 2018 during education in Saint-Petersburg State University of Information Technology Mechanics and Optics. She finished her Bachelor’s degree in Computing machines, complexes, systems, and networks with a thesis about the investigation of the efficiency using wavelet transformations in algorithms of video compression and joined our team as a full member.

Ekaterina develops machine learning models for decision making and the infrastructure for delivering our product to users.

In her free time, Ekaterina explores the world: manages her own investments, learning languages and windsurfing.

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