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High-Tech Women in Science and TechnologyFrom 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
We are a vibrantscience and technologycompany
Oncology &Immuno-Oncology
Neurology & Immunology
Fertility
Patientsare the center of ourwork
Healthcare
Our portfolio addresses therapeutic areas such as:
General Medicine& Endocrinology
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:
Future MobilityCreating a
vibrant worldSmart Technologies
Performance Materials
Title of Presentation | DD.MM.YYYY
Merck Digital
How Stuti’s journey started
High-Tech Women in Science and Technology | 04.03.20
Chicago (U.S.A)
Darmstadt (Germany)
New Delhi (India)
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
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
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
A data scientist’s journey: a personal account of what we have learntWhat 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
A data scientist’s journey: a personal account of what we have learntWhat 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.
A data scientist’s journey: a personal account of what we have learntWhat 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
A data scientist’s journey: a personal account of what we have learntWhat 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
A data scientist’s journey: a personal account of what we have learntWhat 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
A data scientist’s journey: a personal account of what we have learntWhat 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
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
CommunicationCompute infrastructure
What is next?
High-Tech Women in Science and Technology | 04.03.20
A data scientist’s journey: a personal account of what we have learntWhat we like
High-Tech Women in Science and Technology | 04.03.20
Unique/Ever Changing
Drive Important Decisions
Work with some really awesome people
A data scientist’s journey: a personal account of what we have learntTake 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!
