Marius Johan Franco Dioli Email & Phone Number

United States

New York, New York, United States

Currently in the Equity Capital Markets (ECM) team evaluating investments in companies in every sector. Best part of the job is meeting founders of great companies. Previously on the equity side I've worked in the Basic Industries & Autos team, as well as the Tech and Media equity team (Tequities if you're feeling silly). Outside my main role I help shape.

New York, United States

I perform large scale data analysis on medical records, as well as aid in planning research projects, in the research group of Dr. Jie Jane Cao.

Copenhagen, Capital Region, Denmark

Built software to simulate cellular dynamics in the small and large intestines. Currently have a manuscript under review, with publication hopefully in 2025.

London, England, United Kingdom

Worked in the Shops team investigating the relationship between customer purchase behaviour and app latency.

Oslo, Norway

Legal tech which aimed to build a writing tool for legal professionals.

Oslo, Norway

I was involved in two projects: 1) I executed a proof-of-concept study for automating voting in Annual General Meetings using machine learning (ML). My proposed model would be able to automate 90% of cases.2) As part of a team I developed a machine learning pipeline for one-click training, testing, and deployment of ML models.

Trondheim, Sør-Trøndelag, Norway

Techrail aims to modernise tunnel inspection with the use of LiDAR and machine learning. While at Techrail I: - Wrote multiple successful applications for funding, e.g. with Innovation Norway and The Norwegian Research Council totalling over 220k USD.- Developed novel software to analyse and compare LiDAR scans of tunnels for maintenance purposes. - Led.

Oslo, Norway

Responsibilities included making reports and dashboards to aid decision-makers in improving the job portal of the Norwegian Labour and Welfare Administration.

Oslo, Norway

Worked together with the Product Area Work team to develop an anonymisation solution that was able to detect twice as much Personally Identifiable Information (PII) in text as the previous solution. It can be found at https://github.com/navikt/laundromat, and is written in Python. It uses a combination of Machine Learning based Natural Language Processing.

Shanghai, China

- Analysed customer service data, particularly the completion times of past customer service tickets, to identify potential efficiency gains and optimize workflow.- Worked with the marketing team to create visualisations of customer segments and their purchasing habits.- Collaborated with the IT team to build a recommendation engine that suggests similar.

Master Of Science - Ms, Data Science

Currently writing my Master's thesis on how missing data causes bias and discrimination in AI models.

Bachelor In Mathematics, Statistics

Activities and Societies: CogitoBachelor thesis on missing data: https://github.com/mjdioli/bachelor_thesis