The main difference between the top 10% of Data Scientists and the bottom 90% is a distinction most people overlook: Data Storytelling. No matter who you are, you’re going to have a message that you want other people to hear. Often they are product managers, other data scientists, marketing folks, user researchers or execs. Great Data Scientists start by providing insights that have value to the business. However, insights provide no value if they stay in your head! Communicating data science effectively to your business partners is crucial.
As a Data Scientist, you have this amazing tool kit at your disposal: an array of statistical techniques, algorithms, and more computational power than you know what to do with. However, all of your shiny cool skills will go to waste if you don’t provide information that is relevant to your stakeholders. Simply, a job isn’t paying you to construct a huge neural net, they are paying you to provide value towards a business decision.
Our workshop is geared towards anyone who is a current Data Scientist, Business Analyst, Growth Analyst, Analytical Manager or aspiring data professionals. Sorry no Data Ninjas allowed.
This course won’t teach you how to code Random Forests (type of decision tree algorithm), but we will go over how Random Forests can influence others to implement your data insights.
No laptop required, but highly recommended to following along with slides and participation in the labs.
Familiarity with any analytical tool of your choice (Excel, Pandas, Tableau, Google Sheets, etc). During our first lab, we will analyze a fresh data set.
9:15 AM – Arrival Time – Coffee & Small Bites (15 Min)
9:30 AM – Lecture 1 – Data Science In The Wild (1 Hour)
10:30 AM – Break (15 Min)
10:45 AM – Lecture 2 – Derivation (1 Hour)
11:45 AM – Lab/Break – Clothing Sales Data Set (1 Hour, 15 Min)
1:00 PM – Lecture 3 – Presentation (45 Min)
1:45 PM – Lab/Break – Clothing Sales & Presentation (1 Hour)
2:45 PM – Outro/End Of Course
Module 1: State of the Union: Data Science In Business
What’re we doing here?
How to take this course
What is Data Science? What is it not?
What is the role of Data Science in Business?
Types of Data Science in Business
Data Science Teams
Time spent as a Data Scientist
Structuring Data Science projects
Module 2a: Derivation
What is Data Science Derivation?
Ramping up with your business
Prescribing Actionable Change
Module 2b: Derivation Lab + Lunch
Given a data set, use your data powers to solve a prompt
Module 3a: Presentation
What is Data Science Presentation
Starting with Main Points
Tune Tone and Abstraction
Picasso Bull Series
Preparation and Common Curve Balls
Module 3b: Presentation Lab
Using the tools that we’ve covered. Present your findings from the Derivation lab
A strong foundation of how data science works in the real world (structure, teams, deliverables, etc)
The mindset required to “get in the shoes” of your stakeholders to ultimately guide their business goals
Tools and techniques for effectively communicating a data story to a non-data audience
Tons of take home resources for post-course reading
Two 30-minute mentorship sessions (See Below)
Each student who completes “Mastering Your Message” will receive Two 30 min mentorship sessions (Initial meeting + Follow up). Often students will have additional questions and curiosities that need 1 on 1 attention. These mentorship sessions are a chance to ask about course material, seek advice on career goals, or talk more data.
Greg Kamradt is a Senior Growth Analyst on the Product Data Science Team at Salesforce. The Product Data Science team is an amazing group of data scientists who are building predictive apps for internal and customer use cases. We also utilize our apps and analyses to help with trial conversions, targeted marketing campaigns, generate pipeline, close deals, cross-sell/upsell, and reduce attrition.
Prior to Salesforce, Greg was a financial analyst at high tech and online media companies. He earned a degree in Business from Loyola Marymount University. Before joining Salesforce, Greg transformed his analyst skill-set to a data science skill-set during a rigorous 3 months of training in the Galvanize Data Science Immersive in San Francisco. Greg’s data interests include user behavior, time-series, and spatial-temporal analysis. On the weekends you can find Greg in Tahoe, Yosemite, or making pizza.