Disrupt yourself, develop yourself, datacate yourself

1. Think digital, think 3Ds with Henrica Makulu
∙ ECOCASH HOLDINGS DATA SCIENTIST ∙
∙ NUST APPLIED MATHS ALUMNI ∙
∙ LINKEDIN LEARNING INSTRUCTOR ∙

2. My techimony - walk with me…
GenY: 1981-2000
2004-6
• High school: fees
issues
• Got 8 points at A
Level
2007-12
• More fees issues
• Repeated in uni
degree
• Didn’t know what
I wanted to be
• Got a 2.2
2018-20
• Joining Econet
• Initial denied visa
• The WFH year
2012-17
• Stuck in an
unfulfilling job
• Driver’s License
denied 12 times
2021+
• Promoted to Data
Scientist
• Technical writer
• TechWomen Fellow
• LinkedIn Learning
Instructor
There is no success without failure…

4. I just spent 5 weeks in Silicon Valley!
A bit more about me…
4K+ APPLICATIONS
112SELECTED
6ZIMBABWEANS
1ECOCASHIAN!
2012 : MY FIRST APPLICATION
4 = NUMBER OF TIMES I APPLIED

8. 8
...digitize yourself, or become irrelevant!
Disruption
Development
Data
What comes to my mind when I think…
3Ds
DIGITAL

9. The future of careers is different: be future ready
Artificial Intelligence
(self driving cars, Google home, robots, drones etc)
Business powerhouses are big data users
Disruption

10. 2018-20
Data Scientist
2026-27
(2 years)
2028-2032
(5 years)
Data Science
Head
2033
Data Analyst
Analytics/Technology
Executive
Chief Analytics
Officer
2021-25
(5 years)
current
Development

11. Skill Goal Preferred Tools
Score 20.10.2020
Score 27.4.2021
Comment
Data Scrubbing Be able to clean a dataset using Python Python 100% 100%
1 Remove unwanted (duplicate or irrelevant) observations Python 100% 100%
2 Fix structural errors (typos, inconsistent capitalization or mislabeled classes) Python 100% 100%
3 Handle outliers Python 100% 100%
4 Handle missing data Python 100% 100%
Data Exploration Be able to generate and investigate data questions and identify variable trends and relationships for a business problem
Python 78% 95%
1 Select important variables and remove unwanted variables Python 95% 100%
2 Understand the relationship(s) or lack of, between variables Python 60% 90%
Feature Engineering
Create variables to feed into a deployable predictive model Python 34% 54%
Feature engineering for structured data Python 63% 83%
1 Create indicator variables based on the business context Python 50% 75%
2 Create interaction/derived variables Python 50% 75%
3 Create change variables which look at how behavior and/or activity is changing overtime Python 25% 50%
4 Categorise (e.g combine sparse classes in categorical features) Python 100% 100%
5 Add dummy variables for categorical features Python 100% 100%
6 Select important variables and remove unwanted variables i.e feature selection Python 50% 100%
Feature engineering for unstructured data Python 5% 25%
1 Apply appropriate data mining technique(s) to handle various forms of data Python 10% 25%
2 Create and select variables Python 0% 25%
Data VisualisationDesign a satisfactory dashboard (satisfactory = no more than 3 changes from review) Qlik Sense 60% 90%
Machine LearningBuild a deployable predictive model Python 50% 60%
1 Build model Python 50% 60%
2 Evaluate model Python 50% 60%
Artificial Intelligence
Complete a deployable NLP project Python 0% 10%
1 Build model Python 0% 10%
2 Evaluate model Python 0% 10%
Develop through skills

12. 2021 2023 2025
2022 2024
Faith
•Grow closer to God
Education
•Start my Masters
Leisure
•Travel out of Zim
Financial
•Buy more stocks
Fitness
•Work out weekly
Friendships
•Share Christ
Career
•Be a data scientist
Home
•Be more hospitable
Read bible daily
Apply for 4
scholarships
Travel to
Maldives (Sept)
Purchase 3 new
stocks
Work out weekly
-Certify
-Get promoted
Host 1 person a
month
Share my faith
with at least 1
person
Read bible daily
Ladies Speaker
Apply for PhD
3 new holiday
destinations
-Offshore
investment
Own property
-Work out weekly
-Be on a board
-Industry Leader
Host bible studies
& ladies events
Share my faith
with more
people
Read bible daily
Apply for 4
scholarships
1 local
destination
Purchase land
Work out 3
times a week
-Build a model
Be kind even
when tired
Share my faith
with at least 1
person
Develop an action plan

13. From January 2020 to date we have
managed to service 50 clients,
almost half of whom are in the food
industry. This is a slight decline
(17%) from the 56 clients we served
in 2019. Please find attached a
detailed breakdown by industry
5
13
26
24
25
13
0% 20% 40% 60% 80% 100%
2019
2020
Manufacturing Food Clothing
2020: 50 17% YoY
2019:
56
Data!

14. …if you torture the data long enough it will confess
Go to www.menti.com and use the code 9135 6231
Time for real time data!

15. THINK DIGITAL, THINK 3DS
Disrupt yourself Develop yourself Datacate yourself
1 2 3

16. THANK YOU!