Stories from Industry: How can Cognitive Science Programs enable students to succeed - PowerPoint Presentation

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Stories from Industry: How can Cognitive Science Programs enable students to succeed

Jeremy Reynolds

Senior Data Scientist Lead

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Agenda

Background

My Path & Background – why it’s relevant

Lessons learned at a Start-Up: Individual Contributions

Lessons learned post-Acquisition: Managerial Contributions

Future Steps

Conclusions

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Why is my Background important?

I have a variety of experiences at most levels of academia, and in both individual contributor and manager roles in industry.

It gives me a different perspective on the value of Cognitive Science programs and how the programs could help enable students to pursue the right career path.

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Academic Background

PhD in Psychology (2005)

NRSA-funded post-doctoral

f

ellow (2005-2008)

Assistant Professor (2008-2014)

Fundamental Interest: Understanding neural and computational mechanisms underlying higher cognition

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Transitions…

Personally, I was not good at setting boundaries

When I was doing work, I was worried about being a good father and husband

When I was at home, I was worried about supporting students and helping colleagues

Question: Would I be happy performing the role of a faculty member for the next 15 years

?

Answer: I no longer knew

. The answer was no longer a definitive yes.

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Decisions

Very long time between “I don’t know” and even the first step of casually looking at opportunities

I eventually found something that fit my skill set and interests

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Revolution Analytics

Made “R” enterprise-ready by adding scalable learning algorithms and libraries that provide portability and reproducibility.

Professional Services: Consultant / Trainer role – I would go to various clients and deliver training (i.e. teach) and help them solve research problems (i.e. research).

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Microsoft

Microsoft acquired Revolution Analytics in Spring of 2015, and I’ve worked for MS since

Senior Data Scientist Lead

Basically just means I’m a technical manager who works with other data scientists

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Why does my industry experience matter?

I’ve seen the skills necessary to succeed at both the level of an individual contributor and as a manager, and I know, first hand, what kinds of growing pains there are.

Lessons are purely anecdotal, but they are consistent with other anecdotes that you can find online

Survey Results on Academia and Industry

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Being an Individual Contributor

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How do you get hired in industry?

Depends somewhat on the position, but I’ll focus on the analyst / data scientist role

First step: Get Hired

Step 1: Don’t sell yourself short! Apply for things that sound interesting to you or that you think you would be good at, even if you don’t have all of the skills that are listed. You have a wealth of expertise and experience that companies find valuable.

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Your competition: Computer Science (as an isolated discipline), Physics, Statistics, and a few other science domains.

What generally differentiates you from these individuals?

Differentiators

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Data Platform Experience

Relational Databases

Big data stores / Distributed Computing (Hadoop file system specifically)

Version Control

git

Data Mining Approaches

Ensemble methods – recursive partitioning (decision trees), random forests, gradient boosted trees, etc.

Potential Gaps

These are all gaps that can be filled through self study

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Understanding statistics/inference is still incredibly important

Writing/Reporting is still incredibly important

Communication/Presenting is still incredibly important

Once you get one, what can you expect?

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You can still ask potentially interesting questions, you just don’t necessarily have the same ability to drive the questions.

Potential questions

Sentiment analysis of real-time streams

Predictors of credit card fraud

Predictive maintenance

Predicting which customers (or students) are likely to drop from a service (or out of school)

What is different about an industry analyst position?

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Academia

Stability

Theory

Freedom

Flexibility

Industry

Potential impact

Teamwork

Compensation

Boundaries/ExpectationsRelative Strengths

https://www.linkedin.com/pulse/academic-vs-industry-careers-guy-lebanon

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Questions about being an Individual Contributor

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Being a Manager

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Is at a University (as a faculty member) and at Microsoft.

Experience is confounded, so keep that in mind

University

Just assumed that we had the knowledge and experience

Even if we did, or do, it’s completely anecdotal, and not clear that our identified solutions were remotely close to optimal

Microsoft

Large internal management training program, trouble is finding time to take them

A HUGE existing organization, so there are many processes in place

My manager experience

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Parallels across Academia and Industry

Career development within academia is largely a shift in roles from an individual contributor to a manager.

Program / Project management – getting tasks done in a timely fashion

Person management (students, post-docs, RAs)

Regardless of career path – skills in these areas are gaps across virtually all areas of academia. Students and grad students just do not get much formal training in these, unless they’re explicitly pursuing business-oriented degrees in parallel

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Tools / Software

Numerous tools, but the most common is just Excel (or Google Sheets)

Approaches

Organizational responsibilities and accountabilities

Monitoring Status, Agile, etc.

Research

http

://

www.pmi.org/Learning/academic-research/ongoing-research.aspx

Data-driven field of research around best practices and effectivenessIt’s not just setting appropriate goals, especially when you have are relying on a team.Project Management

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Reporting and “Visibility”

Academia: Progress reports (departmental, funding,

etc

)

Industry: Live dashboards, weekly reports about activities

Differences in Managing across Domains

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Leading a team to accomplish goals

Any amount of formal training would be hugely beneficial

Monthly brown-bags

Courses in business school

There is quite a bit of research on this as well…

Person Management

Library search of personnel management

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Questions about Management differences?

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Future Steps andConclusions

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General Preparation

Irrespective

of career path, any type of formal training in management would be exceedingly valuable to trainees (e.g. excellent candidate for NRSA development / course plan

).

They almost certainly will encounter these scenarios

Encourage trainees to ask “meta” questions.

Not just about research track and projects – it is also about understanding what uncertainty means and what the relevant trade-offs are across different career paths

Understand Valuable skills and Gaps

Differentiators in the industry marketplace

GapsProvide Support

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Understand the pros and cons across both career tracks

Understanding current strengths and weaknesses in current training programming

General Strengths: Statistical thinking and understanding of uncertainty, Data Analysis Experience,

Differentiating Strengths: Experimental Design, Causal Inference

Gaps

Management (personnel and project)

Technology-oriented gaps: data platforms, version control

How to help students

Conclusions

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Thank you.

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