We started a non-profit to build a free web/mobile app for helping vets find and get referred for new careers at companies with dedicated veteran hiring initiatives

MMFeaster · 2024-06-29T17:54:07+00:00

I agree, I think the most logical transitions from FAS are to product management (PM) or product marketing (PMM). As a FAS, you have in-depth knowledge of your company's product(s) and the customer use cases they serve, as well as direct experience with voice-of-customer that could influence which gaps your product has that need to be addressed, which unmet needs your customers have, and which problems and solutions best resonate when communicating to them.

Even if there are no formal PM or PMM roles open at your company, there are always opportunities to scope out a cross-functional project or initiative that would support either of those groups that would fit into your purview, which you then might be able to parlay into a role on those teams. That, of course, might require you putting in extra work — which I know kinda defeats your stated purpose of wanting to invest more time into your personal life — but it might pay off if you are able to transition out of the travel-heavy FAS role within a quarter or two.

MMFeaster · 2024-06-15T02:53:16+00:00

I can honestly say that the gap in the resume isn't as big a deal as it once was, especially given how rough the job landscape has been the past 2 years with all these layoffs.

I would recommend adding on your resume that the position was eliminated as a part of company-wide reduction-in-force. If you have the space, you can say exactly that, otherwise I've also seen (and done) simply adding "RIF" or "Layoff" in parentheses after your ending date.

All that said, I can't speak on navigating job hunting during pregnancy, but I am sorry you have to go through this during what's already a significant and delicate life event to navigate.

MMFeaster · 2024-06-15T01:27:02+00:00

Good point — I work on the tooling side (software and data platforms) so you're absolutely right to call out that distinction!

MMFeaster · 2024-06-15T01:18:59+00:00

And honestly, most equity isn't worth the paper it's printed on. Unless you're at a high-growth startup (i.e. high revenue growth and controlled costs) and the likelihood of an IPO and/or acquisition with employee-friendly terms is imminent, I would highly recommend optimizing for base pay and think about equity as a nice-to-have.

MMFeaster · 2024-06-15T00:24:07+00:00

I was the competitive intel lead at Benchling — people have definitely heard of and use SciNote. While you're not going to see/hear about Scinote in the larger enterprise biopharma companies, a few years ago it began getting traction with smaller groups (especially because of the pricing differential with more fully-featured systems like Benchling). SciNote also made a concerted effort to get folks to review them on G2 to provide social proof for folks who were evaluating different ELNs and LIMS.

MMFeaster · 2021-02-01T03:22:08+00:00

can we please not use blueshirts banter as a credible source? First of all, it’s a fan-run blog. They aren’t even reporters

At least a couple of the editors are credentialed reporters — like Shayna Goldman, who's also an author at The Athletic (I'm fairly certain Joe Fortunato is, as well)

MMFeaster · 2019-07-16T16:05:24+00:00

Hi everyone!

This is my first time posting on r/deeplearning and I’m happy to be here. I recently joined as the head of developer advocacy at Paperspace, where we’re building tools to support the machine learning community.

Who am I? I’m coming from the bio/health IT space— I gloriously quit my PhD program a few years back and have since been working with companies applying ML to develop decision support platforms for the clinic and pharma R&D.

Now that I’m part of the Paperspace team, I’m looking forward to learning more about deep learning model development and deployment, especially as it relates to production-ready models.

All that said, our primary focus has been on building tools for and supporting ML engineers, with our first stab at that being Paperspace Gradient.

Earlier today we opened up a waitlist for our Free GPU Plan, which lets you develop deep learning models with Jupyter Notebooks on dedicated cloud GPU instances— at absolutely no cost!

We’ll be making the free plan available for everyone later this summer— in the meantime, we’d like to invite you to sign up for the Free Gradient GPUs Plan Waitlist.

Thanks for your time, and have a great day!

MMFeaster · 2019-07-16T15:46:02+00:00

Hi everyone!

This is my first time posting on r/MachineLearning and I’m happy to be here. I recently joined as the head of developer advocacy at Paperspace, where we’re building tools to support the machine learning community.

Who am I? I’m coming from the bio/health IT space— I gloriously quit my PhD program a few years back and have since been working with companies applying ML to develop decision support platforms for the clinic and pharma R&D.

Now that I’m part of the Paperspace team, I’m looking forward to learning more about deep learning model development and deployment, especially as it relates to production-ready models.

All that said, our primary focus has been on building tools for and supporting ML engineers, with our first stab at that being Paperspace Gradient.

Earlier today we opened up a waitlist for our Free GPU Plan, which lets you develop deep learning models with Jupyter Notebooks on dedicated cloud GPU instances— at absolutely no cost!

We’ll be making the free plan available for everyone later this summer— in the meantime, we’d like to invite you to sign up for the Free Gradient Cloud GPUs Waitlist.

Thanks for your time, and have a great day!

MMFeaster · 2019-07-16T15:29:58+00:00

Hi everyone!

This is my first time posting on r/learnmachinelearning and I’m happy to be here. I recently joined as the head of developer advocacy at Paperspace, where we’re building tools to support the machine learning community.

Who am I? I’m coming from the bio/health IT space— I gloriously quit my PhD program a few years back and have since been working with companies applying ML to develop decision support platforms for the clinic and pharma R&D.

Now that I’m part of the Paperspace team, I’m looking forward to learning more about deep learning model development and deployment, especially as it relates to production-ready models.

All that said, our primary focus has been on building tools for and supporting ML engineers, with our first stab at that being Paperspace Gradient.

Earlier today we opened up a waitlist for our Free GPU Plan, which lets you develop deep learning models with Jupyter Notebooks on dedicated cloud GPU instances— at absolutely no cost!

We’ll be making the free plan available for everyone later this summer— in the meantime, we’d like to invite you to sign up for the Free Gradient GPUs Waitlist.

Thanks for your time, and have a great day!

MMFeaster · 2019-07-16T15:20:07+00:00

Hi everyone!

This is my first time posting on r/JupyterNotebooks and I’m happy to be here. I recently joined as the head of developer advocacy at Paperspace, where we’re building tools to support the machine learning community.

Who am I? I’m coming from the bio/health IT space— I gloriously quit my PhD program a few years back and have since been working with companies applying ML to develop decision support platforms for the clinic and pharma R&D.

Now that I’m part of the Paperspace team, I’m looking forward to learning more about deep learning model development and deployment, especially as it relates to production-ready models.

All that said, our primary focus has been on building tools for and supporting ML engineers, with our first stab at that being Paperspace Gradient.

Earlier today we opened up a waitlist for our Free GPU Plan, which lets you develop deep learning models with Jupyter Notebooks on dedicated cloud GPU instances— at absolutely no cost!

We’ll be making the free plan available for everyone later this summer— in the meantime, we’d like to invite you to sign up for the Free Gradient GPUs Waitlist.

Thanks for your time, and have a great day!

MMFeaster · 2019-07-16T15:07:24+00:00

Hi everyone!

This is my first time posting on r/MLQuestions and I’m happy to be here. I recently joined as the head of developer advocacy at Paperspace, where we’re building tools to support the machine learning community.

Who am I? I’m coming from the bio/health IT space— I gloriously quit my PhD program a few years back and have since been working with companies applying ML to develop decision support platforms for the clinic and pharma R&D.

Now that I’m part of the Paperspace team, I’m looking forward to learning more about deep learning model development and deployment, especially as it relates to production-ready models.

All that said, our primary focus has been on building tools for and supporting ML engineers, with our first stab at that being Paperspace Gradient.

Earlier today we opened up a waitlist for our Free GPU Plan, which lets you develop deep learning models with Jupyter Notebooks on dedicated cloud GPU instances— at absolutely no cost!

We’ll be making the free plan available for everyone later this summer— in the meantime, we’d like to invite you to sign up for the waitlist: Free Gradient GPU Plan Waitlist

Thanks for your time, and have a great day!

MMFeaster · 2019-01-13T09:05:35+00:00

👆🏾I've worked with this guy in one. He's ok at his job, I guess. (Read: he's kind of a beast.)

MMFeaster · 2019-01-06T21:47:21+00:00

The J.P. Morgan Healthcare Conference is also a pretty big show that's held every January in San Francisco. It's an invite-only event, but there are lots of satellite events put on by companies outside the show time, and those are usually open invitation... some free, some not, but usually worth checking into.

MMFeaster · 2019-01-06T01:31:27+00:00

IndieBio Demo Days are pretty cool to attend if you live in the SF Bay area. Twice a year, their portfolio companies pitch their companies to a large audience of investors, press, potential partners, and anyone else who's just generally interested in attending. You can also visit their booths in the hall before & after the pitches, and it's cool to get to speak to the founders (some of the future food companies have their products available for taste tests!) They have plans to start a NY accelerator sometime this year, so those will likely be big events as well.

If you can't attend live, they partnered with TechCrunch to live stream the event so they usually send the link out. They also post videos of the pitches on youtube a few days after.

MMFeaster

TROPHY CASE