Transitioning to a career in data science requires careful planning and smart choices. In this session, I'll help you understand how to switch to data science. Using my own experiences and what I've learned from the industry, we'll break down the important steps for a successful transition. We'll cover everything from figuring out which skills you can carry over to learning the technical stuff and connecting with other professionals. By the end, you'll have the knowledge and tools you need to start your journey into data science, whether you're a seasoned professional looking for something new or just starting out in the field.

1. My Journey From the Field of
Oil & Gas, To The Exciting
World of Data Science
Presented by: Omar Ossama

2. Our Clients Include

3. • Bachelor’s degree in Petrochemicals & Gases Engineering.
• Started as a Petroleum Inspector at Saybolt Egypt.
• Transitioned to roles such as Performance Analyst and Global Operations
Analyst at SWVL.
• Led performance and data analysis efforts at DigiSay.
• Currently serving as a Data Science Consultant and Managing
Consultant at Synapse Analytics.
• Pursuing a Master's in Data Science and Artificial Intelligence at the
University of London.
Career Overview

4. The Allure of the
Oil & Gas Field
• Enjoyable work environment
with supportive colleagues
who became lifelong friends.
• Found the job relatively easy,
leveraging my skills effectively.
• Flexibility in working on-call,
providing downtime when
work was scarce.
• Attractive financial
compensation package.

5. Why I left Oil
& Gas Field
• No fulfilment or
passion.
• Repetitive work with
no personal growth.
Why I Chose
Data Science
• Fascination with
programming.
• Stumbled upon
Artificial Intelligence.
• Learning about Data
Science.

6. Postgraduate In Data Science
What I learned:
Learned to do EDA and how to apply the different algorithms on
different types of datasets.
Pros:
• Time efficient.
• Comprehensive
overview.
Con:
Focused on applying
techniques without in-
depth theory.

7. Taking the Data Science Plunge
• Learned what to look for and how to find actionable
insights from the data.
• Found the difference between what I learned in the courses
and what the reality of Data Science is.
• Building my first predictive model.
• Convincing management to adopt the model.
My job as a Performance Analyst at SWVL; a fantastic
introduction to the business side of data analysis.

8. Why I Enrolled In A Master’s Degree
• Desire to have a deeper understanding of the inner workings of Data
Science.
• Preference for a structured course over online courses.
• Ability to fund my studies.
• Prestige.
Cons of Studying For a Master’s Degree
• Expensive if not on a scholarship.
• A lot of self study.
• Sacrifice work-life balance. Time is more valuable than
money.

9. I GOT LAID-OFF

10. Insights into
My Brief Stay
• Joined DigiSay to spearhead the
Performance and Data Analysis
department.
• Departed due to a perception
that the focus on data wasn't a
priority within the company's
agenda at that time.

11. • Constant learning experience
• Working with customers from different fields
and at different stages of data maturity.
• The models we’ve built at Synapse Analytics
⚬ Optical Character Recognition (OCR).
⚬ Credit Scoring.
⚬ Inventory Management.
⚬ Dynamic Pricing.
⚬ Customer Churn.
⚬ Recommendation Engines.
Life at Synapse Analytics

12. Practical Lessons from years
of Data Science work
• Data science is software written by data.
• Data possesses an expiration date.
• Anticipating misunderstandings from colleagues or clients regarding
data requirements is crucial for project success.
• Constant Communication between data scientists and business
stakeholders is indispensable for the success of models.
• In structured courses, algorithm building often dominates the workload,
but in real-world scenarios, data cleansing typically constitutes most of
the tasks.
• Feature engineering is a data scientist’s bread and butter.

13. Tips for Landing a Job in Data Science
Start with SQL and either Python or R with a
target to learn all 3 later-on.
Go beyond the coursework
Understand the needs of the business you are
interested in and demonstrate your understanding.
Show interest in the field and a desire to grow