{ "media_type": "text", "post_content": "Finance undergrad + MBA. No tech background. Pure business consulting experience. Looking to do a Masters of Data Science to make the pivot (may or may not stay in consulting). Thoughts?", "post_id": "6079be44fdf574001d522a5c", "reply_count": 8, "vote_count": 1, "bowl_id": "5ace5097be6e660013abcc42", "bowl_name": "Data & Analytics Consultants" }

Finance undergrad + MBA. No tech background. Pure business consulting experience. Looking to do a Masters of Data Science to make the pivot (may or may not stay in consulting). Thoughts?

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Pivot to what role? What you need to become a data scientist alongside math PhDs may not be the same as what you need to be on the business side handling SQL and data visualization.

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Developing data strategy, leading data transformation initiatives and being a part of the Chief Data Office. Eventually lead teams of data scientists.

A lot of hiring managers look down on DS or Analytics Masters. I'd recommend doing MSCS or Stats instead.

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I doubt I could pivot to a master in CompSci or Stats without an undergrad.

M1 and DS1 are absolutely right. Most DS degrees are nothing but cash grabs but at the same time, you don't need a full fledged degree to get a lot of analytics roles. A lot of them are just intermediate SQL jobs that with the right work experience, you should be able to get

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Since you're already an SM, you might not need another degree. Use your business background to exit to a transformation office or internal strategy team of a F500. Make the business case for data projects, and execute those projects. By then (if you aren't already), you'll be too senior or too well paid to just be leading a team of data scientists.

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I am definitely looking at that option. I do feel a bit out of my depth with data projects. I know a majority of the transformations at large F500 firms will have a strong data backbone to it. I want to make sure I am able to be hold my own. PS. Always have been a very detail-oriented person. A bit allergic to the consulting fluff even though I have gotten much better at it.

Course included are: - Designs of Algorithms and Programming for Data - Machine Learning - Management of Big Data and Big Data Tools - Data Mining and Prescriptive Analysis - NLP - Bayesian Statistics and Machine Learning - Deep Learning

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