SEI Novus is a portfolio intelligence platform where asset owners and asset managers interact with their investments and with each other. We help investors enrich and manage their data, extract actionable investment insights, and improve stakeholder communication via visualization and automation. We strive to be the center of the institutional investment ecosystem: where the world’s greatest investors gather to manage their portfolios and engage with one another.
$120 trillion is invested annually on behalf pensions, endowments, sovereign funds, private investors, and family offices. These groups strive to affect the world in unique ways—be it through funding scholarships, protecting pensions, establishing charitable foundations, supporting medical research, preserving wealth, and more.
Unfortunately, many of these institutions are using outdated and disconnected tools to manage their portfolios. SEI Novus offers comprehensive solutions for the multi-asset class portfolio. By providing a single platform that streamlines data processes, quantifies investment skill, uncovers bias, and helps investors plan more accurately, we are helping investors amplify their impact.
We expect our team members to deliver on their responsibilities and understand how each and every component of our company works to generate our collective success. We hold ourselves and our colleagues accountable to the highest standards.
If the following sounds like you, we look forward to getting to know you—
Over the last few years, there has been a growing influx of capital in Private Equity funds. Given the rising importance of this asset class, investors have requested more and more transparency on the underlying investments of said funds, both to better understand to which industries/geographies they are exposed and to assess the managers’ skill in a more rigorous way.
So far, the exchange of information between managers and investors has been incredibly inefficient. The information regarding the underlying investment is contained in Quarterly Reports, which are PDF files dozens of pages long with formats changing wildly between managers. Aggregating the data from these documents has historically been an extremely time-consuming and error-prone process, often offshored for cost saving reasons.
We decided to take a different approach to this problem, and over the last couple of years we have developed and started using an OCR tool capable of cutting the processing time of said documents by around 50%. We have reached the point where only minor purely IT optimizations of the workflow are possible, and major efficiency gains would only be attainable through a change of paradigm.
So far, the slowest part of the process has been gathering data contained in the text, as our workflow is already quite efficient when it comes to tables. Analysts still have to read the documents page by page to find relevant bits of information and manually annotate the original document to tell the OCR tool that a particular word or phrase needs to be extracted, and what it means.
Leveraging our fast-growing corpus of already 2’000 manually annotated documents, we want to apply NLP techniques to this problem. Over the course of this project, the Data Science Intern will select, build and train an NLP model to automatically annotate predefined target entities within the free text of the Quarterly Reports. The goal is to implement a proof-of-concept / experimental pipeline which submits the automated annotations to the analysts’ check, in a machine-assisted, human-supervised fashion.
Critical Skills / Abilities
Novus looks for a Data Science Intern in Zurich, KS location.
The proposed salary for Data Science Internship position at Novus is Not disclosed.
According to the common industry standard, Data Science Internship specialist is in charge for the following activities.
To be disscussed with candidate
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