Episode #14
Richard Copsey, Open Innovation Manager (Part 2)
Jan 6, 202020 minS1
In part 2, we further discuss the role of the gig economy via the crowd in data science and machine learning, now and in the future.
Loading…
Loading…
Technology
Hosted by Dr. R. A. Leo Elworth · Technology · EN · 14 episodes
This podcast series was put together by data science intern Leo Elworth to spread knowledge on these hot topics to the broader community. As the buzz around data science and machine learning continues to grow, more and more people are developing a curiosity for these topics, as well as their applications to the specific field of oil and gas. Interviews with expert data scientists and geologists serve to highlight innovative problems and share entertaining anecdotes. Podcast editing assistance was provided by Selena Garza.
Required Pod Score for this show. PitchCentric checks your profile against host openness, topical fit, and audience signals before you generate a pitch.
Contact path
Verified email
Booking probability
19%
Guest openness
Selective
Sign up to generate a grounded pitch for Data Science and Machine Learning in Oil and Gas.
Signup to Generate a PitchData Science and Machine Learning in Oil and Gas is a technology podcast hosted by Dr. R. A. Leo Elworth, with 14 episodes on record and a Required Pod Score of 80. PitchCentric scores this show on Booking Probability, Listen Score, and live audience signals refreshed every 24 hours.
Dr. R. A. Leo Elworth hosts Data Science and Machine Learning in Oil and Gas, a technology show with 14 episodes published.
Our AI reads these to draft pitches. Use them as grounding for a pitch that cites a real guest and a specific topic.
Episode #14
In part 2, we further discuss the role of the gig economy via the crowd in data science and machine learning, now and in the future.
Episode #13
Richard Copsey introduces the idea of looking "beyond the walls" for data science and machine learning solutions. New approaches like crowdsourcing can bring data science work in from a wide, external talent pool. We also discuss three specific oil and gas problems that were solved in part by the crowd.
Episode #12
In part 2, we get tips from Jenny for how to be a successful entrepreneur in the startup space of data science and machine learning. For instance, we cover the dos and don'ts of navigating a tech showcase as a startup.
Episode #11
Jenny Johnson discuss how to work with emerging technologies in data science and machine learning. In particular, she walks through working with startups, and more generally the startup ecosystem, to solve business pain points requiring new data science and machine learning solutions.
Episode #10
How does a machine learning skeptic turn into a machine learning advocate? In Part 2, Matt recounts his data science and machine learning journey from his initial introduction and skepticism to his acceptance and forward looking thoughts on where these methods will proceed from here in oil and gas.
Recent guests on Data Science and Machine Learning in Oil and Gas. Study who booked and why before you pitch.
Sponsor detection runs nightly. Check back soon.
Based on semantic analysis of episode topics and host coverage, this show is a strong guest fit for executives in:
Industry fit is computed by PitchCentric using vector embeddings of the show's episode catalog.
Is this podcast yours and you'd like to remove or correct details? Request removal or email privacy@pitchcentric.com.
FAQs
If you have a concern about deliverability, AI quality, data privacy, or whether this will actually work for your specific situation, it's probably answered below.
Founder Solo gives you 50 AI pitches per month using the credit model (Standard pitches cost 1 credit, Enriched pitches cost 2). Founder Pro raises that to 200 credits per month and adds full Booking Probability access, unlimited Magic Match, Apollo enrichment credits, and data export capabilities. Both plans use the same credit system, so you can stretch your monthly budget further by using Standard-mode drafting.
Agency tiers have no base fee. You pay per managed client and per talent profile. Agency Standard is $199 per client per month; Agency Pro is $399 per client per month. Both add $39 per talent profile per month. Your own team's user seats are always free.
A talent profile represents one person (founder, executive, or spokesperson) you are booking onto podcasts. It includes their bio, topics, headshots, and outreach history. Team plans include 5 profiles; agency plans are pay-as-you-go.
Yes, at any time. Upgrades take effect immediately; downgrades apply at the end of the current billing period. Contact support if you need help migrating between plan families.
Every paid plan includes a 15-day free trial. Your card is saved at signup but you will not be charged until day 16. Cancel any time from your dashboard.
You keep access until the end of your current billing period. No charges after that. Your data is retained for 30 days in case you reactivate.
Yes. Select Annual on the pricing toggle and the discounted price is applied automatically at checkout. The annual price shown is the full year cost.
That is our Enterprise tier. Contact our sales team and we will build a custom plan with volume pricing, a dedicated account manager, and SLA guarantees.
