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First of her name – Being the first data scientist in your company
First of her name – Being the first data scientist in your company
Inbar is a Data Science Team Leader at Snappy, a fast-growing gifting platform. She was the first data person to join the company and built its data science team.
Before joining Snappy, Inbar worked as a data scientist, data engineer, and backend developer in the tech industry and the IDF (unit 8200 & “Mamram”). She is most interested in NLP and FemTech and is the proud mom of a 2-year-old rescue pup.
Noa is an AI & machine learning consultant working with data for over a decade. She works with both startups and larger companies and helps them use their data to drive business success. She also leads the community of WiDS Israel and is passionate about FemTech and promoting female entrepreneurship.
Inbar is a Data Science Team Leader at Snappy, a fast-growing gifting platform. She was the first data person to join the company and built its data science team.
Before joining Snappy, Inbar worked as a data scientist, data engineer, and backend developer in the tech industry and the IDF (unit 8200 & “Mamram”). She is most interested in NLP and FemTech and is the proud mom of a 2-year-old rescue pup.
Noa is an AI & machine learning consultant working with data for over a decade. She works with both startups and larger companies and helps them use their data to drive business success. She also leads the community of WiDS Israel and is passionate about FemTech and promoting female entrepreneurship.
Being a company’s “First Data Scientist” – is it a fantastic opportunity to upgrade your career or a waste of your time?
In this session, we will discuss the good, the bad, and the ugly about being the first data scientist in your company how to recognize the actual day-to-day work when receiving an offer, what could be your obstacles, how to solve them, and what kind of opportunities this role could create for us.
We will discuss tips on what you should know and do when there is no one else to consult with or learn from, especially the first things to do in your new position. We will also share our very own ‘lessons learned, from our experience as an in-house first data scientist (Inbar) and a consultant (Noa), bringing DS where it hasn’t been before.
Being a company’s “First Data Scientist” – is it a fantastic opportunity to upgrade your career or a waste of your time?
In this session, we will discuss the good, the bad, and the ugly about being the first data scientist in your company how to recognize the actual day-to-day work when receiving an offer, what could be your obstacles, how to solve them, and what kind of opportunities this role could create for us.
We will discuss tips on what you should know and do when there is no one else to consult with or learn from, especially the first things to do in your new position. We will also share our very own ‘lessons learned, from our experience as an in-house first data scientist (Inbar) and a consultant (Noa), bringing DS where it hasn’t been before.
| 8:45 | Reception |
|---|---|
| 9:30 | Opening words by WiDS TLV ambassadors Or Basson and Noah Eyal Altman |
| 9:40 | Dr. Kira Radinski - Learning to predict the future of healthcare |
| 10:10 | Prof. Yonina Eldar - Model-Based Deep Learning: Applications to Imaging and Communications |
| 10:40 | Break |
| 10:50 | Lightning talks |
| 12:20 | Lunch & Poster session |
|---|---|
| 13:20 | Roundtable session & Poster session |
| 14:05 | Roundtable closure |
| 14:20 | Break |
| 14:30 | Dr. Anna Levant - 3D Metrology: Seeing the Unseen |
| 15:00 | Aviv Ben-Arie - Counterfactual Explanations: The Future of Explainable AI? |
| 15:30 | Closing remarks |
| 15:40 | End |
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