Five Mindsets to Succeed as a Data Scientist IRL

Pallav Agrawal,Director, Data Science

Levi Strauss & Co.

I WANT TO KNOW YOU

What do Data Scientists Create?

Create Concise Generalizations

“90 percent of the data in the world today has beencreated in the last two years alone”- IBM Marketing Study

https://twitter.com/Johnny_Uzan/status/1031742658048352257

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Data Science

Data Science is a lot like Observational Astronomy

-- Occam’s razor

Develop a really good BS Filter

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https://www.facebook.com/dan.ariely/posts/904383595868

Companies with ‘.ai’ domains raise 3.5x more money

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https://twitter.com/xaprb/status/930674776317849600

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Data Science

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“To ascend this pyramid fast…”

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“First build this pyramid you must…”

AI StartupsExecutives

The Dunning-Kruger Effect

‘AI’ as a Service powers the Flywheel….

https://callingbullshit.org/

“Bullshit involves language, statistical figures, data graphics, and other forms of presentation intended to persuade by impressing and overwhelming a reader or listener, with a blatant disregard for truth and logical coherence.”

Learn to Think Like a Lawyer

What is a Sandwich?

Is this a Sandwich?

Is this a Sandwich?

Is this a Sandwich?

Is this a Sandwich?

Is this a Sandwich?

Are any of these a Sandwich?

“SANDWICHES” AS USED IN ARTICLES 47 AND 48 OF TITLE 12, C.R.S. ARE DEFINED AS SINGLE SERVING ITEMS SUCH AS HAMBURGERS, HOT DOGS, FROZEN PIZZAS, BURRITOS, CHICKEN WINGS, ETC.”

- Colorado Department of Revenue, Liquor Enforcement Division

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“I know it, when I see it”

What about Fraud Detection?

Or Predicting CLTV?

It often helps to frame a problem statement like a Legal Contract

Kozyrkov’s Razor“When decision-makers don’t realize

that thinking deeply is their job, remind them.”

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Utilize UI/UX to Improve CX

“FB Messenger Bot was unable to understand 70% of customer queries”- Motley Fool

“41% of consumers say they stopped shopping with a company because of “poor personalization.”-Accenture

Design for Trust

Encourage User Feedback

Show, Don’t Tell

Wizard of Oz Testing Start with an MVP

“You have to start with the customer experience and work backwards to the

technology”Steve Jobs

Three (timeless) books to get you started

Data Science is a Team Sport

Types of Data Science Practiced Today:

Marketing/PR Centric: Where the hype around ‘AI’ is used to improve perception of an aging company among Wall Street Analysts

Types of Data Science Practiced Today:

Marketing/PR Centric: Where the hype around ‘AI’ is used to improve perception of an aging company among Wall Street Analysts

Research Centric: Where the discovery of new algorithms is central to maintain the company’s competitive advantage

Types of Data Science Practiced Today:

Marketing/PR Centric: Where the hype around ‘AI’ is used to improve perception of an aging company among Wall Street Analysts

Research Centric: Where the discovery of new algorithms is central to maintain the company’s competitive advantage

Recruiting Centric: Where the only way the company can attract the best minds is through “look at all this cool AI we are doing!”

Types of Data Science Practiced Today:

Marketing/PR Centric: Where the hype around ‘AI’ is used to improve perception of an aging company among Wall Street Analysts

Research Centric: Where the discovery of new algorithms is central to maintain the company’s competitive advantage

Recruiting Centric: Where the only way the company can attract the best minds is through “look at all this cool AI we are doing!”

Ego-Centric: Where the CEO wants to appear a visionary at Techcrunch Disrupt by unloading a bunch of Singularity references

Types of Data Science Practiced Today:

Marketing/PR Centric: Where the hype around ‘AI’ is used to improve perception of an aging company among Wall Street Analysts

Research Centric: Where the discovery of new algorithms is central to maintain the company’s competitive advantage

Recruiting Centric: Where the only way the company can attract the best minds is through “look at all this cool AI we are doing!”

Ego-Centric: Where the CEO wants to appear a visionary at Techcrunch Disrupt by unloading a bunch of Singularity references

Business Centric: Where the most important business decisions are made using insights derived from the scientific use of data

Types of Data Science Practiced Today:

Marketing/PR Centric: Where the hype around ‘AI’ is used to improve perception of an aging company among Wall Street Analysts

Research Centric: Where the discovery of new algorithms is central to maintain the company’s competitive advantage

Recruiting Centric: Where the only way the company can attract the best minds is through “look at all this cool AI we are doing!”

Ego-Centric: Where the CEO wants to appear a visionary at Techcrunch Disrupt by unloading a bunch of Singularity references

Business Centric: Where the most important business decisions are made using insights derived from the scientific use of data

Data Science as a

Team Sport

Business-Centric Data Science is a Team Sport

Cheerleader

Business Stakeholder

Customer Insights

DevOps

Project Manager

Technical Product Manager

Data Scientist

Data Engineer

UI/UX

Data Analyst

Subject Matter Expert

Roadmap DevelopmentCustomer

Business Technology

Roadmap DevelopmentCustomer

Business Technology

Desirability

I want:

● Free 1-hour delivery on orders● Beyonce’s look from Coachella● To experience the feel of the

garment virtually

Roadmap DevelopmentCustomer

Business Technology

Desirability

I want:

● Free 1-hour delivery on orders● Beyonce’s look from Coachella● To experience the feel of the

garment virtually

Viability

Roadmap DevelopmentCustomer

Business Technology

Desirability

I want:

● Free 1-hour delivery on orders● Beyonce’s look from Coachella● To experience the feel of the

garment virtually

Viability Feasibility

Roadmap DevelopmentCustomer

Business Technology

Desirability

FeasibilityViability

I want:

● Free 1-hour delivery on orders● Beyonce’s look from Coachella● To experience the feel of the

garment virtually

Ideation Uncovering Automation Opportunities:

If I could identify/recognize/interpet _____________________________________________

in __________________________________________,

I could _____________________________________.

Hint: sources could include anything from images, video, audio, text or a mix of these.

http://milkandhoney.ai/

Ideation Uncovering Prediction Opportunities:

If I could predict precisely how much/many _____________________________________________ at any given moment, I could _____________________________________________.

Hint: identify places where you currently rely on estimates and averages to make decisions.

If I could predict the fastest way to _____________________________________________ at any given moment, I could _____________________________________________.

Hint: identify processes that require moving something from point A to point B with multiple paths to choose from.

http://milkandhoney.ai/

RECAP

Data Science is the process of extracting concise and actionable insights from data through scientific rigor

Practice healthy skepticism towards most remarkable claims, and cautious optimism towards the applicability of positive results

Before executing, first craft a precise problem statement developed with decision makers using data and subject matter expertise

Focus on improving the customer experience by making the customer journey intuitive and frictionless

Learn to communicate and collaborate within interdisciplinary teams to build products that lie at the intersection of desirability, viability and feasibility

Questions?

Are you doing analytics or statistics? Cargo Cult science?Some Key Principles • use many data sources (the plural of anecdote is not data) • understand how the data were collected (sampling is essential) • weight the data thoughtfully (not all polls are equally good) • use statistical models (not just hacking around in Excel) • understand correlations (e.g., states that trend similarly) • think like a Bayesian, check like a frequentist (reconciliation) • have good communication skills (What does a 60% probability even mean? How can we visualize, validate, and understand the conclusions?)

Data science produces insights about people

Machine learning produces predictions for people to use

Artificial intelligence produces actions to help people

- David Robinson, Chief Data Scientist at DataCamp

What the team depends on a Technical Product Manager for:- Vision and Roadmap Development- Customer Needs and Wants- Ideation and Solutioning- Goal Setting: KPI’s, OKR’s- Domain Knowledge- Technical Fluency- Cross-Functional Communication

In the absence of whom, these responsibilities are delegated to the most willing, or remain unfulfilled.

TPM

Data Science

Data Eng.

UI/UX

Project Manager.

Biz

Customer Insights