A data scientists journey: a personal account of what we have - - PowerPoint PPT Presentation

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A data scientists journey: a personal account of what we have - - PowerPoint PPT Presentation

Oct 08, 2023 209 likes •433 views

A data scientists journey: a personal account of what we have learnt Stuti Agrawal and Eleonora Lippolis High-Tech Women in Science and Technology From Cybersecurity to Artificial Intelligence | 04.03.20 We are a vibrant science and

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High-Tech Women in Science and Technology From Cybersecurity to Artificial Intelligence | 04.03.20 Stuti Agrawal and Eleonora Lippolis

A data scientist’s journey: a personal account of what we have learnt

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We are a

vibrant science and technology company

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Oncology & Immuno-Oncology Neurology & Immunology Fertility

Patients

are the center of our work

Healthcare

Our portfolio addresses therapeutic areas such as:

General Medicine & Endocrinology

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Genome Editing Food and Beverage Biologics

We help scientists to

solve problems

at every stage of their work

Life Science

We offer solutions in fields such as:

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Future Mobility

Creating a

vibrant world

Smart Technologies

Performance Materials

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Title of Presentation | DD.MM.YYYY

Merck Digital

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How Stuti’s journey started

High-Tech Women in Science and Technology | 04.03.20

Chicago (U.S.A) Darmstadt (Germany) New Delhi (India)

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Darmstadt (Hessen, Germany) Noci (Puglia, Italy) Pavia (Lombardia, Italy) Erlangen (Bayern, Germany )

How Eleonora’s journey started

High-Tech Women in Science and Technology | 04.03.20

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What we thought | What we found

High-Tech Women in Science and Technology | 04.03.20

  • Clean data
  • Enough data
  • Easily available data
  • Balanced data
  • Lot of data cleaning to be

performed

  • There is never enough data
  • Enterprise system and

multiple locations

  • Unbalanced data

What we thought What we learnt

Data collection

A data scientist’s journey: a personal account of what we have learnt

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What we thought | What we found

High-Tech Women in Science and Technology | 04.03.20

  • Only need of data and

technical skills

  • Understanding the context is

very important

  • Need of immersion in the

business What we thought What we learnt

Understanding business problem

A data scientist’s journey: a personal account of what we have learnt

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A data scientist’s journey: a personal account of what we have learnt What we thought | What we found

High-Tech Women in Science and Technology | 04.03.20

What we thought What we learnt

Understanding business problem Compute infrastructure

  • All data already

ingested and ready to be used

  • No Linux based computer
  • No data ingestion
  • AWS machines
  • Fragmented infrastructure
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A data scientist’s journey: a personal account of what we have learnt What we thought | What we found

High-Tech Women in Science and Technology | 04.03.20

What we thought What we learnt

Understanding business problem Stakeholder buy-in

  • Everyone wants data

science and has a clear idea of how they want to implement it in their business.

  • People are either sold TOO

MUCH or NOT AT ALL to data driven ideas. In both cases, the “HOW?” is not answered.

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A data scientist’s journey: a personal account of what we have learnt What we thought | What we found

High-Tech Women in Science and Technology | 04.03.20

What we thought What we learnt

Trust

  • Need to build trust as

experts

  • Never occurred
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A data scientist’s journey: a personal account of what we have learnt What we thought | What we found

High-Tech Women in Science and Technology | 04.03.20

What we thought What we learnt

Understanding business problem Knowing the problem we are solving

  • People give you data and

expect results without a clear goal

  • Need consulting skills to

ask the right questions

  • When we build a

model, we know what we are trying to achieve

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A data scientist’s journey: a personal account of what we have learnt What we thought | What we found

High-Tech Women in Science and Technology | 04.03.20

What we thought What we learnt

Understanding business problem Knowing the problem we are solving Model building

  • Build fancy Machine

Learning models

  • Don’t need the best model,

but something better that what exists

  • Start simple
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A data scientist’s journey: a personal account of what we have learnt What we thought | What we found

High-Tech Women in Science and Technology | 04.03.20

What we thought What we learnt

Understanding business problem Knowing the problem we are solving Communication

  • Build model, get

results and provide them

  • Critical thinking
  • Lot of interactions
  • Different languages
  • How the results matter

in business context

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Trust

High-Tech Women in Science and Technology | 04.03.20

Data collection Model building Stakeholder buy-in Understanding business problem Knowing the problem we are solving Communication Compute infrastructure

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What is next?

High-Tech Women in Science and Technology | 04.03.20

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A data scientist’s journey: a personal account of what we have learnt What we like

High-Tech Women in Science and Technology | 04.03.20

Unique/Ever Changing Drive Important Decisions Work with some really awesome people

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A data scientist’s journey: a personal account of what we have learnt Take home message

High-Tech Women in Science and Technology | 04.03.20

Do not search for a clear path to become a data scientist: there is none! With every project you will learn something new!

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Thank you for your attention!

stuti.agrawal@merckgroup.com

Stuti Agrawal

eleonora.Lippolis@merckgroup.com

Eleonora Lippolis