u/Longjumping-Pass-973

I’ve gone from an overall size L to M over the past year (both top and bottom), lost weight pretty steadily, and my band size has definitely gone down 2 inches… but my cup size?? Literally unchanged. My tits did not get the memo at all.

At this point I feel disproportionately top-heavy as a tripple D compared to the rest of my body. Is there anything that actually helps make breasts smaller besides just continuing to lose overall body fat and praying genetics cooperate? Or is this one of those “you either get lucky or get a reduction” situations?

Also, please drop comments if you did get a reduction (do they grow back? side effects? cost $$ ? etc). I’m in my early 20s so I cannot really afford a reduction right now 😔 but would still love to have the deets.

Would especially love advice from people whose band size shrinks / overall lose weight but cup size stays stubbornly the same.

I’m curious how people successfully transitioned out of the economics/policy research pipeline—especially the RA / predoc / quantitative policy analysis world—and into roles that are more decision-oriented rather than purely technical research, especially without entering any graduate program (i.e. without using a Masters or JD as a pivot).

Background: I’ve spent a lot of time in the typical toolkit ecosystem (R, Python, Stata, Matlab; empirical research; data cleaning; econometrics; policy memos; literature reviews; etc.).

The work is intellectually interesting, but I increasingly feel like I’m sitting several layers away from actual decision-making or implementation.

The paths I’m most interested in are things like:
• Endowment / foundation / allocator investing
• Public-sector strategy or implementation
• Policy execution roles (rather than academic-style analysis)
• leadership / operations strategy
• Crossovers between policy + finance + institutions

What I’m struggling with is that the RA/predoc track seems heavily optimized toward: PhD placement, Academic signaling, Technical rigor, Publishing support, Methodological specialization… but not necessarily toward: Judgment, Stakeholder management, Organizational leadership, Investing intuition, Operational execution, Commercial thinking.

A few questions for people who made this jump:
• What actually translated from your research background, and what didn’t?
• How did you convince employers you were more than “the data/econ person”?
• Were there specific roles that served as better transition points?
• For endowment/foundation investing specifically, how do those teams evaluate candidates coming from policy/econ backgrounds?

I’d especially love to hear from people who moved into: university endowments, foundations, sovereign wealth / development finance, chief of staff / strategy roles, implementation-heavy government work, policy entrepreneurship, mission-driven investing

Would appreciate candid advice, including hard truths about compensation, credential barriers, networking realities, or whether this transition is actually rarer than it appears from the outside.

I’m considering enrolling in either the MS in Applied Data Science or the MS in Financial Mathematics, got into both in a part-time / online format (I am not in Chicago and work full time), and would really appreciate candid perspectives from current students or alumni.

A bit about me:
• Currently work in policy research
• Daily work involves a lot of Python, R, Matlab, and Stata

Long-term goal is to pivot into either:
• finance (strategy, quant, endowment investing, capital markets, etc.), OR
• strategy / public policy implementation roles that are more execution-oriented and analytical

My hesitation with the MS Applied Data Science program is honestly the broader uncertainty around AI and how much of the traditional analytics / DS workflow could get commoditized over the next several years. I know “AI is eating everything” is an oversimplification, but it does make me wonder whether a general applied DS degree will age as well as it once would have.

At the same time, I’m unsure about the reputation and market perception of the MS Financial Mathematics program.

A few questions I’d love insight on:
• How are these programs perceived by employers?
• Which one seems more versatile for someone trying to pivot industries without becoming a pure quant?
• Does the MSFM pigeonhole you into quant finance?
• Does the MSADS actually provide durable signal/value beyond skills that can increasingly be self-taught + AI-assisted?
• How strong are the alumni networks and recruiting pipelines for each?
• For people already working full-time, how manageable are these programs part-time online?

I just had my mid-year check-in and got really positive feedback from my manager and teammates. I honestly can’t stand my team, the work, or the culture here. I keep it professional and do my job, but internally I’m completely checked out and planning to leave ASAP.

So I’m trying to figure out: are managers sometimes just being nice/avoiding conflict to keep things smooth, or is it actually common to be perceived way more positively than you feel about yourself or your situation?

Curious to hear managers’ take on this.

Edit: many people said things can look different in routine check ins vs bigger performance reviews. Well, my team + manager dont do routine check ins at all ✨

Edit: US Based

Hi everyone, I’m hoping to ask this with genuine curiosity and respect—I’m still learning and would really appreciate your perspectives.

I’m a North Indian Brahmin, and I’m currently learning Tamil because I’m getting married to a Tambrahm. I want our future kids to grow up speaking + reading/writing both Tamil and Hindi. Tamil, of course, because that will be a huge part of their identity (their last name will be his after all), and Hindi—not because it’s my mother tongue (it isn’t), but because I was taught it growing up as a way to access a wider part of India. And I’d like them to have that same access by learning Hindi.

For context, my actual mother tongue is a non-Hindi “North Indian” language, but I can speak/understand Hindi (and by extension Urdu), and now—kunjam kunjam Tamizh.

One thing that has surprised me is that I’m able to draw quite a few parallels between Hindi and Tamil (albeit Tambrahm Tamil)—especially with Sanskritam-rooted vocabulary. Even the written scripts, while obviously different, have certain similarities that make recognition easier once you get used to them (tamizh has fewer letters than Hindi—its actually tad bit easier that way). That overlap made the learning process feel faaaar less alien than I initially expected.

Which brings me to my question: why is there such a strong anti-Hindi sentiment?

I want to be clear—I’m not asking this to challenge or dismiss it. I’m trying to understand it better. From the outside, I’m starting to wonder if part of it is tied to historical and political movements like the Dravidian movement / Periyar’s ideas—especially around resisting Brahminism or a more homogenized Bharatiya (dare I say Sanatani) identity?

At the same time, in my home state (I’d rather not give away too much, but it’s North Indian-ish), people are generally quite willing to switch to Hindi (it is most people’s third language or something they picked up, albeit pretty broken, from Bollywood if they never learned in school) if someone doesn’t know the local language. So my lived experience has been more of linguistic accommodation than resistance, which is why the contrast in TN stands out to me.

Note: Posting here and not other tamizh subreddits because I have realized that Brahmin or even caste in general can be a trigger word there (was a shocker to me because in my native state, it’s a crucial part of everyone’s identity that shapes your religious practices, customs, even language/dialect—and nobody from any caste has ever had to “shy away” or “hide” anything).

I’d really appreciate hearing your thoughts—especially from those who have grown up with this context.

Thanks in advance for engaging kindly!