[DSC MENA 24] Omar_Ossama - My Journey from the Field of Oil & Gas, to the Exciting World of Data Science.pptx

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