A data scientist joins a startup and faces several challenges, including a lack of clearly defined goals, communication issues between teams, and not having access to data at the beginning. However, by getting involved in business logic and data modeling, the data scientist can help build the foundation for future data science work. It's important that startups clearly communicate expectations and allow data scientists to design a roadmap to data science work over time.

1. What to do with a
data scientist in
your startup
The challenges and benefits

2. Hi there! I am Xanthippi.
(Aspiring) Data scientist in OCL, working mainly with R.
Graduated from Technical University of Crete, as a Production and Management Engineer
with a specialisation in Operational Research.
Agile and UX enthusiast.
Main goal: To get to a point of combining math and coding for assisting in the development of a
product, which is a result of iterations of UX research, and connecting it with the business needs and
development.
Side-goal : Gaining a better understanding of the world.

3. What about OCL?
OCL it is a UK based startup.
Building a “smart’s contract” framework, expressed as graph, which is distributable,
decentralized and uses cryptography.
“New institutions, and new ways to formalize the relationships that make up these
institutions, are now made possible by the digital revolution. I call these new contracts
“smart”, because they are far more functional than their inanimate paper-based ancestors.
No use of artificial intelligence is implied. A smart contract is a set of promises, specified in
digital form, including protocols within which the parties perform on these promises.”
Nick Szabo, Smart Contracts: Building Blocks for Digital Markets

4. How clearly is DS defined?
● Data analyst
● (Big) Data Engineer
● ML engineer
● BI analyst
● Business analyst
● Researcher
Source https://blog.datasciencedojo.com/data-science-skills/

5. A few challenges when joining a startup
● Not clearly defined goal/purpose
● Communication issues between business and tech team
● When is it going to be live?
● Funding concerns
● Not clearly defined job roles and not clearly defined needs of the startup
● Pivoting, aka throwing your work away

6. When a data scientist joins a startup..
Data science
YOU THE TEAM
¯_(ツ)_/¯ ? source : https://imgflip.com/memegenerator/Skeptical-
Baby

7. Challenges
How to get to the
data science part
Where to start?
How to fit in the
team
Challenges of a
data scientist w/o
data

8. Where to start
You need DATA
Business logic shall be
integrated
The team needs to
“implement” all about
DATA
Becoming
the DATA
person
source : https://www.zdnet.com/article/how-to-build-a-data-science-
team/

9. Finding your way back to data science
source : https://www.analyticsvidhya.com/blog/2016/12/21-reason-why-you-should-not-become-a-data-scientist/
So, far you:
● Are well aware of the business logic
● Have an overview of the data flow
● Were part of the data modeling
You have been building the bridge to data science while walking it.
So, take a step back, “zoom out” and start planning the reporting so you can get
eventually to data science.
Be patient, one step at the time.
Treat it as a product, design a roadmap to get where you want.

10. Why you shouldn’t join a startup
✗ Dealing with uncertainty.
✗ Losing touch with data science. Possibly less than 30% of your time related to data
science, as you consider it.
✗ What you are to deliver is a product, that requires the initial product to be built and get
launched.
✗ You have to be flexible and adaptive.
✗ You have at first to become a generalist, while finding the time to become a specialist.

11. Why you should join a startup
✓ You have an overview of the project and product.
✓ You are well aware of the data modeling and data flow.
✓ You are well aware of limitations.
✓ You might be able to design with the team and implement an end to end data product
as you envisioned it.
✓ You are becoming part of a bigger picture while expanding your understanding .

12. How a data scientist’s life could become
easier
Be well aware and communicate why you want a data scientist to join your team and what
are your expectations.
Allow them to design a roadmap, so they can get to the data science part the “right” way.
The fun for them might start after the product has been launched.
Communicate the business needs.
Be aware that when the time comes they might need to focus on their thing and no longer be
the data person. After all, the “data” thing it is not a one wo(man) show. :-)

13. At the end of the day..

14. Thank you!
LinkedIn : www.linkedin.com/in/xanthippilemontzoglou
Email : xanthippi.lemontzoglou@hotmail.com
Twitter : @xlemontzoglou