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Science to Data Science: PhDs leaving for industry

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Nomisma

Strada Maggiore 44

40125 Bologna

Italy

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Beschreibung des Events

Beschreibung

At some point, most Ph.D. researchers and Postdocs wonder whether to continue or eave for a position in industry. 
More money, time or impact: The motives will vary, and are equally valid.

Data Science and Artificial Intelligence (AI) is the fastest growing job market for the very highly qualified. Together, we explore the career crossroads between research, teaching, and industry:

  • Can I know when to leave?
  • What is my destination?
  • How do I manage the transition?

Workshop participants

You have a highly numerate background in science, engineering, medicine, or economics? Are you curious about the opportunities in Data Science and Artificial Intelligence? Possibly wondering whether an academic career is the best or only choice?

Facilitator

Dr. Chris Armbruster is the Director, Data Science Retreat (Berlin). His role is to select and empower new Data Scientists, working with international candidates. He also initiated a ‘Women & Data Science’ scholarship program. Earlier, Chris tracked the rise of the postdoc as a distinct career stage in Europe; helped the Max Planck Society roll out its digital infrastructure to >80 institutes and >10,000 researchers; and scaled digital products and startups. He is on a mission to find and empower 10,000 data scientists for Europe to develop the next generation of AI-driven products.

The series

In Q1/2018, the 12 workshops had 576 registered participants with feedback collected from 236 attendees.

  • The largest workshops were Heidelberg (109), Bonn (98), as well Tübingen and Göttingen (76).
  • More than 60% think a career change to data science very likely, and more than a quarter are definite about the change.
  • More than 60% want to transition within 12 months or less.
  • More than 80% have prior coding experience with Python or R.
  • 4 out of 10 can imagine being a co-founder of an AI-driven startup.


Workshop structure

00-10 Welcome & workshop objectives

The workshop builds a bridge from Science to Data Science, offering a roadmap for crossing that bridge, which may be personalized by you to ensure a successful entry to the profession in not more than six to nine months.

10-40 Continuity v change; academia v industry

“If I traverse the bridge to Data Science: How much change do I want in my career?” We will discuss the pros and cons of changing careers to data science and artificial intelligence, and highlight the most important changes facing PhDs in a move to industry or startups.

  • Jam session – Academic track record v changing to industry? (Groups of 3-4, 15 min)
  • Plenary session - Pro & Con of change and continuity (15 min)

40-120 A roadmap for your transition as a Data Scientist and AI expert

Ask me anything on your transition to data science and artificial intelligence. We explore a simple but tried-and-tested roadmap:

  1. Exploration of the field: First, get a feel for and understanding of the role of the data scientist by utilizing e.g. courses, hackathons, meetups, and by interviewing practicing data scientists and credible recruiters. For you, this should result in a stop/go decision.
  2. Domain orientation: Which field or industries are you considering? Are you more interested in computer vision, big data or natural language understanding? For health, finance, or automotive industries? As you consider your options, look for indicators as to how high or low the entry barrier is. For example: How new is the product? How large is the industry? Are startups hiring aggressively and must the wider industry follow suit (e.g. autonomous driving)?
  3. Further training (if any): Your interactions will give you an idea if further training is required for a successful transition. If in doubt, you can also interact with training providers (e.g. data science bootcamps) to see what gets their graduates hired in the domain you are interested in.
  4. Career entry: I reckon you want the learning curve to be steep, so a team with a good track record in a vibrant urban environment may be the first choice. A good track record is indicated by e.g. a growing team, team members staying for at least two years or more, a product on the market, and growing revenues.

120-150 Writing an industry-relevant CV to get interviews

What do I mean by industry-relevant CV? A presentation tailored to hiring managers and recruiters or human resources, making it clear just how you and your skills are relevant. Such a document is always individual if not personal. Yet, I can offer the following guidance:

  • The first page should include your mission and search statement, a technical skills overview, and your last employment.
  • The second page includes your education, any other employment, and the transferable skills you bring from academia to industry.


Followed by Dinner

Please join to share your experience, hear more tips & tricks, and stay in touch.

Proof-of-concept

The original proof-of-concept was established together with the Max Planck Society and PhDs from the MPI.

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Datum und Uhrzeit

Veranstaltungsort

Nomisma

Strada Maggiore 44

40125 Bologna

Italy

Karte anzeigen

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