We talked about: Loris’ background Transitioning from physics to data Aligning people on concepts Lead indicators and stickiness Context, semantics, and meaning Communication and being memorable Making data digestible for business and building trust The importance of understanding the language of business Stakeholder mapping Attending business meetings as a data professional Organizing your stakeholder map Prioritizing How to support the business strategy Learning to speak online Resource recommendations from Loris Links: Discovering Data Discord server: https://bit.ly/discovering-data-discord Loris' LinkedIn: https://www.linkedin.com/in/lorismarini/ Loris' Twitter: https://twitter.com/LorisMarini

We talked about: Sadat’s background Sadat’s backend engineering experience Sadat’s pivot point as a backend engineer Sadat’s exposure to ML and Data Science Sadat’s Act Before you Think approach (with safety nets) Sadat’s street cred and transition into management The hiring process as an internal candidate The importance of people management skills The Brag List The most difficult part of transitioning to management Focusing on projects and setting milestones Sadat’s transition from EM to data science management How much domain knowledge is needed for management? The main difference between engineering and management How being an EM helped Sadat transition no DS management 53:32 Transitioning to DS management from other roles How to feel accomplished as a manager Sadat’s book recommendations Sadat’s meetups Links: Sadat's Meetup page: https://www.meetup.com/berlin-search-technology-meetup/ Meetup event "Bias in AI: how to measure it and how to fix it event": https://www.meetup.com/data-driven-ai-berlin-meetup/events/289927565/ ML Zoomcamp: https://github.com/alexeygrigorev/mlbookcamp-code/tree/master/course-zoomcamp Join DataTalks.Club: https://datatalks.club/slack.html Our events: https://datatalks.club/events.html

We talked about: Irina’s background Irina as a mentor Designing curriculum and program management at AI Guild Other things Irina taught at AI Guild Why Irina likes teaching Students’ reluctance to learn cloud Irina as a manager Cohort analysis in a nutshell How Irina started teaching formally Irina’s diversity project in the works How DataTalks.Club can attract more female students to the Zoomcamps How to get technical feedback at work Antipatterns and overrated/overhyped topics in data analytics Advice for young women who want to get into data science/engineering Finding Irina online Fundamentals for data analysts Suggestions for DataTalks.club collaborations Conclusions Links: LinkedIn Account: https://www.linkedin.com/in/irinabrudaru/ ML Zoomcamp: https://github.com/alexeygrigorev/mlbookcamp-code/tree/master/course-zoomcamp Join DataTalks.Club: https://datatalks.club/slack.html Our events: https://datatalks.club/events.html

We talked about: Angelica’s background Angelica’s books Data journalism How Angelica got into data journalism The field of digital humanities and Angelica’s data journalism course Technical articles vs data journalism articles Transforming reports into data storytelling Are reports to stakeholders considered technical writing? Data visualization in articles Article length The process of writing an article Finding writing topics How Angelica got into writing a book (communication with publishers) The process for writing a book Brainstorming Reviews and revisions Conclusion Links: Data Journalism examples (FENCED OUT): https://www.washingtonpost.com/graphics/world/border-barriers/europe-refugee-crisis-border-control/??noredirect=on Data Journalism examples (La tierra esclava): https://latierraesclava.eldiario.es/ Small medium publication aiming at being Stack Overflow of Medium: https://medium.com/syntaxerrorpub Example of a self-published book on Data Visualization: https://www.amazon.com/Introduction-Data-Visualization-Storytelling-Scientist-ebook/dp/B07VYCR3Z6/ref=sr_1_4?crid=4JRJ48O7K8TK&keywords=joses+berengueres&qid=1668270728&sprefix=joses+beremguere%2Caps%2C273&sr=8-4 My novels (in Italian) La bambina e il Clown: https://www.amazon.it/Bambina-Clown-Angelica-Lo-Duca/dp/1500984515/ref=sr_1_9?__mk_it_IT=%C3%85M%C3%85%C5%BD%C3%95%C3%91&crid=2KGK9GMN0FAHI&keywords=la+bambina+e+il+clown&qid=1668270769&sprefix=la+bambina+e+il+clown%2Caps%2C88&sr=8-9 My novels (in Italian) Il Violinista: https://www.amazon.it/Violinista-1-Angelica-Lo-Duca/dp/1501009672/ref=sr_1_1?__mk_it_IT=%C3%85M%C3%85%C5%BD%C3%95%C3%91&crid=12KTF9EF5UKIG&keywords=il+violinista+lo+duca&qid=1668270791&sprefix=il+violinista+lo+duca%2Caps%2C81&sr=8-1 Course on Data Journalism: https://www.coursera.org/learn/visualization-for-data-journalism ML Zoomcamp: https://github.com/alexeygrigorev/mlbookcamp-code/tree/master/course-zoomcamp Join DataTalks.Club: https://datatalks.club/slack.html Our events: https://datatalks.club/events.html

We talked about: Nikola’s background Making the first steps towards a transition to BI and Analytics Engineering Learning the skills necessary to transition to Analytics Engineering The in-between period – from Marketing to Analytics Engineering Nikola’s current responsibilities Understanding what a Data Model is Tools needed to work as an Analytics Engineer The Analytics Engineering role over time The importance of DBT for Analytics Engineers Where can one learn about data modeling theory? Going from Ancient Greek and Latin to understanding Data (Just-In-Time Learning) The importance of having domain knowledge to analytics engineering Suggestion for those wishing to transition into analytics engineering The importance of having a mentor when transitioning Finding a mentor Helpful newsletters and blogs Finding Nikola online Links: Nikola's LinkedIn account: https://www.linkedin.com/in/nikola-maksimovic-40188183/ ML Zoomcamp: https://github.com/alexeygrigorev/mlbookcamp-code/tree/master/course-zoomcamp Join DataTalks.Club: https://datatalks.club/slack.html Our events: https://datatalks.club/events.html

We talked about: About Anna and METRO Anna’s background The importance of a technical background for data product owners What are product owners? Product owners vs product managers Anna’s work on recommender systems at METRO Expanding the data team Types of algorithms used for recommender systems What kind of knowledge and skills data product owners need to have Problems and ideas should come from the business How Anna handles all her responsibilities The process for starting work on new domains Product portfolio management ProductTank and Anna’s role in it Anna’s resource recommendations Links: Data Science for Business Book: https://www.amazon.de/-/en/Foster-Provost/dp/1449361323/ref=sr_1_1?keywords=data+science+for+business&qid=1666404807&qu=eyJxc2MiOiIxLjg3IiwicXNhIjoiMS41MiIsInFzcCI6IjEuNDYifQ%3D%3D&sr=8-1 Article on Data Science Products: https://www.linkedin.com/pulse/way-create-data-science-products-lessons-learnt-anna-hannemann-phd/ ML Zoomcamp: https://github.com/alexeygrigorev/mlbookcamp-code/tree/master/course-zoomcamp Join DataTalks.Club: https://datatalks.club/slack.html Our events: https://datatalks.club/events.html

We talked about: Audience Poll Andrey’s background What data science practice is Best DS practice in a traditional company vs IT-centric companies Getting started with building data science practice (finding out who you report to) Who the initiative comes from Finding out what kind of problems you will be solving (Centralized approach) Moving to a semi-decentralized approach Resources to learn about data science practice Pivoting from the role of a software engineer to data scientist The most impactful realization from data science practice Advice for individual growth Finding Andrey online Links:  Data Teams book: https://www.amazon.com/Data-Teams-Management-Successful-Data-Focused/dp/1484262271/ ML Zoomcamp: https://github.com/alexeygrigorev/mlbookcamp-code/tree/master/course-zoomcamp Join DataTalks.Club: https://datatalks.club/slack.html Our events: https://datatalks.club/events.html

We talked about: Sonal’s background How the idea for Zingg came about What Zingg is The difference between entity resolution and identity resolution How duplicate detection relates to entity resolution How Sonal decided to start working on Zingg How Zingg works What Zingg runs on Switching from consultancy to working on a new open source solution Why Zingg is open source Open source licensing Working on Zingg initially vs now Zingg’s current and future team Sonal’s biggest current challenge Avoiding problems with entity/identity resolution through database design Identity resolution vs basic joins, data fusions, and fuzzy joins Deterministic matching vs probabilistic machine learning Identity and entity resolution applications for fraud detection Graph algorithms vs classic ML in entity resolution Identity resolution success stories What Sonal would do differently given the chance to start over with Zingg Advice for those seeking to realize their own solution to a data problem Reading suggestion from Sonal Conclusion Links: Open-Source Spotlight demo "Zingg":https://www.youtube.com/watch?v=zOabyZxN9b0 Creative Selection: Inside Apple's Design Process During the Golden Age of Steve Jobs book: https://www.amazon.com/Creative-Selection-Inside-Apples-Process/dp/1250194466 ML Zoomcamp: https://github.com/alexeygrigorev/mlbookcamp-code/tree/master/course-zoomcamp Join DataTalks.Club: https://datatalks.club/slack.html Our events: https://datatalks.club/events.html

We talked about: Tomasz’s background What Tomasz did before DataOps (Data Science) Why Tomasz made the transition from Data science to DataOps What is DataOps? How is DataOps related to infrastructure? How Tomasz learned the skills necessary to become DataOps Becoming comfortable with terminal The overlap between DataOps and Data Engineering Suitable/useful skills for DataOps Minimal operational skills for DataOps Similarities between DataOps and Data Science Managers Tomasz’s interesting projects Confidence in results and avoiding going too deep with edge cases Conclusion Links: Terminal setup video, 19 minutes long: https://www.youtube.com/watch?v=D2PSsnqgBiw Command line videos, one and a half hour to become somewhat comfy with the terminal: https://www.youtube.com/playlist?list=PLIhvC56v63IKioClkSNDjW7iz-6TFvLwS Course from MIT talking about just that (command line, git, storing secrets): https://missing.csail.mit.edu/ ML Zoomcamp: https://github.com/alexeygrigorev/mlbookcamp-code/tree/master/course-zoomcamp Join DataTalks.Club: https://datatalks.club/slack.html Our events: https://datatalks.club/events.html

We talked about: Katie’s background What is a data scientist? What is a data science manager? Quality of the craft How data leaders promote career growth Supporting senior data professionals Choosing the IC route vs the management route Managing junior data professionals Talking to senior stakeholders and PMs as a junior The importance of hiring juniors What skills do data scientist managers need to get hired? How juniors that are just starting out can set themselves apart from the competition Asking senior colleagues for help and the rubber duck channel The challenges of the head of data Conclusion Links: Jobs at Gloss Genius: https://boards.greenhouse.io/glossgenius ML Zoomcamp: https://github.com/alexeygrigorev/mlbookcamp-code/tree/master/course-zoomcamp Join DataTalks.Club: https://datatalks.club/slack.html Our events: https://datatalks.club/events.html