Work for data scientists in high finance ?
1) What roles in the industry exist for data scientists?
There has been quite a lot of discussion on the rising importance of programming / data science skills within finance; however, I don't see too many advertised data roles or companies specialising in this area.
the few I can think of is data scientists inside equity research teams at bulge-brackets; systematic funds
2) Is it realistic being a self-employed independent contractor providing data science services to clients within high finance?
3) Any ideas of high-value / in-demand services that could be provided?
Some ideas I've had include:
-Market research (macro forecasting, industry-specific)
-Ad-hoc research projects for investment managers
-NLP/ Sentiment analysis of stocks
-Processing or selling altdata (eg geolocation, credit/debit card)
-Data visualization for investment co's
-Risk management visualizations
-Visualisations in industry research reports put out by M&A boutiques
-Automating some business development / acquisition processes
-Alt data processing, blending in finance to generate ER reports, sell the data/reports
-Asset Backed Securities/Mortgage Backed Securities, consumer loan pools valuation and projections, etc.
I don't think being an independent contractor for any high level role in finance is feasible, period. If you have talent the firms want you to work for them specifically.
Second the above, there is plenty of data science work to be done, but it won't be as an independent contractor. Finance data is extremely sensitive and they will not let you work for anyone else.
Off the top of my head Citi has a financial strategy group that advises IBD, is heavy on data science and includes a lot of what you listed. A lot of banks will run this type of work through India teams.
A number of potential angles in PE on both the investing / ops sides, but the clearest one IMO is in the middle market, where disproportionate value can be generated in significantly upgrading portco data operations / infrastructure and beginning to leverage actionable insights from the newly-gathered data. Someone with a data science background would likely be able to add value at a firm that prioritizes a similar approach.
And then adding to that, many currently-investable businesses are continually discovering on their own that data aggregation and analysis is increasingly important to their abiilities to compete, whether it's volumes of POS data, marketing analytics, etc., and I would assume that there will be a corresponding increase in strategy roles oriented towards data science. Access to high-quality market research data for any given industry in that context is very valuable, too.
Ex aut enim vel sunt minus voluptatem quia. Eligendi doloremque iste doloremque perferendis consectetur. Voluptas maxime dolorem nisi enim praesentium molestiae aut. Est nesciunt enim facilis distinctio maxime aliquid aut.
Et distinctio non debitis cumque harum tempora. Eaque omnis est eveniet sequi.
Vero aliquam ut excepturi dolorem quaerat expedita voluptas accusantium. Ut quia aliquam ad nesciunt sed voluptatem voluptatum quisquam. Aut beatae a harum earum. Sed enim enim doloremque rerum quis accusantium aperiam dolor.
Temporibus voluptatem iure necessitatibus amet voluptatem pariatur nisi. Debitis voluptatem sed dolorem rerum officia consequuntur voluptatem. Soluta assumenda et sed voluptas dolorem qui. Est qui hic et accusamus nulla sapiente ab. Quis aut accusantium aut vel. Aut tempore reiciendis rem id ut hic quia quidem.
See All Comments - 100% Free
WSO depends on everyone being able to pitch in when they know something. Unlock with your email and get bonus: 6 financial modeling lessons free ($199 value)
or Unlock with your social account...