A day in the life in Data Analytics and Data Science

In this article, we will explore a day in the life of a Data Analyst with Bella Lanczki and a day in the life of a Data Scientist with Miguel Silva. We will learn, what is the difference between Data Analytics and Data Science, how Data Scientists spend their time at work, What are the daily tasks of a Data Analytics professional, and explore Data Science and Data Analytics career paths and opportunities. These departments work closely together and help ExoClick provide Ad Network insights to its clients and help them achieve the highest revenue from their advertising campaigns through understanding and sharing advertising trends and future predictions. So let’s get to know these two departments to see what working with Data looks like at ExoClick. 

What is the difference between Data Analytics and Data Science and How do Data Analytics and Data Science benefit a business?

Data Science and Analytics play a significant role in the tech industry, as quantifiable data helps us to understand emerging trends. Data Analytics tends to focus more on analyzing past data to help with the decision-making process at present, while Data Science often involves using data to build models that can predict future outcomes. An Ad Network with a Data team is an advantage for Advertisers and Publishers because it can share insights into consumer behaviors. The Data Analytics and Data Science departments can provide statistics on the devices used to make purchases for any period and identify developing trends in the industry. This helps increase ROI as Advertisers understand their target demographic better allowing for deeper and more specific targeting leading to better campaign results. For example, The Top Verticals and Traffic Sources in China for Chinese New Year was an article that had original statistics and information from the ExoClick platform that helped Advertisers get the most out of their offers during Chinese New Year. The information came from the Data Analytics team and enabled data-driven decision-making by providing Advertisers with a list of the high-converting offers in China during the event.

Bella: Analytics at ExoClick

Bella works as a part of the Analytics Team at ExoClick, we will now look into a day in life as a Data Analyst.

“Hi Bella, we are so excited to see what a day in the life in Data Analytics looks like here at ExoClick.”

Q1 Can you tell us what a day in the life in Data Analytics looks like and what are the daily tasks of a Data professional at ExoClick?

A: A day in the life in Data Analytics, usually entails collecting, cleaning, and analyzing data to provide numerical insights for other departments at ExoClick. Utilizing statistical techniques and data visualization, I present patterns and trends in data to colleagues. This helps the company get insights into the areas of strength and where we can improve. I then verify the findings with the team and communicate the data “mean” (or average) to ensure all data is presented correctly and effectively.

Q2 Can you share a successful data-driven project you have worked on?

A: One of the notable projects I have worked on involved selecting campaigns for the Smart Bid project. Smart Bid is a campaign pricing model on the ExoClick network. It uses machine learning to determine the optimal price for your bid in real-time based on the likelihood of conversion and analysis across different data points and dimensions such as device type, zones, and GEOs. I identified high-volume campaigns and curated a subset to train our machine-learning model. This helped ensure Advertisers got the highest revenue for their bid and increased their campaign revenues.

Q3 How do you maintain accuracy and reliability in data analysis?

A: To produce an accurate analysis, I first clean the data and address any missing values. This is a crucial step as missing data can lead to inaccurate results. Once the data has been processed, I verify the results by utilizing the company’s internal platforms such as Back Office or Admin panel. In some cases, I may only need to examine specific data tables within our database. However, in situations where the accuracy of the results is difficult to determine, I will discuss the findings with my team to ascertain the best course of action to verify the results. By taking these steps, we can ensure that the analysis is reliable and trustworthy.

Q4 How do you communicate findings to non-technical teams?

A: Data Analytics is very numerical, for me this is great because I understand and find numbers interesting. When we need to communicate this to other teams such as our Account Managers, we employ data visualization for clarity and present the data clearly in Excel tables for simple reports. We can also offer dashboards for broader team access, ensuring our new features and insights are easy for all to track and understand.

Q5 What motivated you to pursue a career in Data Analytics with ExoClick?

A: I believe Data Analytics jobs in online advertising are very rewarding. There are a lot of  Data Analytics career paths and opportunities especially here at ExoClick. My role at ExoClick allows me to address real-world challenges by leveraging data and analytical tools for solutions. The dynamic nature of the field offers continuous learning opportunities and professional growth. I appreciate the creative problem-solving aspect and collaborative environment that comes with working in Data Analytics. Also, working for ExoClick has given me the opportunity to learn about Data and the Advertising industry and I get to use my Computer Science knowledge at the same time. I also find the company environment at ExoClick to be positive with a fantastic team that helps me whenever I need it. There are also some great perks like the 360-degree view of Barcelona and a free monthly massage that are just the icing on the cake!

“Thank you Bella for taking the time to show us what a day in the life in Data Analytics at ExoClick looks like!”

Miguel: Data Science at ExoClick

So, now let’s talk to Miguel, a member of our Data Science department, and see what a day in the life of a Data Scientist entails and how it differs from the role of an Analyst.

“Hi Miguel, thank you for taking the time out of your busy schedule to answer a few questions on Data Science.” 

Q1 To start, could you tell us a bit about a day in the life of a Data Scientist, how do Data Scientists spend their time at work and stay ahead of the game?

A: A day in the life of a Data Scientist is very interesting. Our primary focus daily is to build models that can analyze current data and make predictions on unseen data. Online advertising jobs in Data Science utilize Machine Learning algorithms to uncover hidden patterns within the vast amount of data generated by ExoClick daily. For example, the machine does not know what a word such as “Portugal” actually means! It’s our interpretation that brings meaning to the value. We need to understand which are the useful features and characteristics of the collected data and represent them numerically. 

Q2 What tools and technologies do you typically use daily for Data Science?

A: Data Science and Machine Learning are increasing in importance across many industries. We process information and store it for the machine to learn the trends in the industry. I collaborate with other Data Scientists and the analytics team to create accurate data analysis and manipulation. There are a lot of good tools that have been developed and standardized for the industry. Tools I use daily include AWS S3, Jupyter, and SciPy. I also use programs that have been developed on top of the Python programming language like Pandas to help us extract the right information to make future predictions. 

Q3 How do you ensure the accuracy and reliability of your machine learning models for ExoClick/What are the daily tasks of a Data professional?

A: Ensuring the accuracy and reliability of our machine learning models is crucial for demonstrating the value and benefits to ExoClick. We approach this by dividing the model evaluation process into four key phases:

1. Firstly, we define relevant metrics such as accuracy, precision, and recall to assess the model’s performance in predicting discrete events. We incorporate business-related metrics to measure the model’s impact on factors like revenue.
2. The second phase involves offline testing to select the best model based on non-business metrics and assess its generalization capabilities.
3. Next, we conduct A/B testing by deploying the model on a small portion of company traffic and evaluating its impact using business metrics.
4. Finally, before deploying the model in production, we continuously monitor both offline and business metrics to prevent any performance degradation. 

Q4 How do you collaborate with other engineering teams within the organization?

A: Once we have a trained model that can do inference, this model needs to be included in the overall processes of ExoClick which is where other engineering teams assist. They develop the infrastructure that calls the models we develop and measure the impact of our model in areas such as auction response time.

Q5 Why did you choose a career in Data Science and what are your favorite aspects of your job here at ExoClick?

A: I enjoy extracting knowledge from data: questioning and transforming data to reveal details about the complex processes shown in the data. With Data Science, a greater focus is placed on probability and understanding of the data, creating and testing hypotheses, and increasing knowledge of complex systems, which is then reflected by training better models. There are also many Data Analytics career paths and opportunities in AdTech. The benefits of working at ExoClick include the ability to leave my mark on how Data Science and machine learning are developed within the company. I have a very talented and thorough team around me that provides a second opinion and advice when needed. When I got the chance to meet senior members of staff within ExoClick, I felt a lot of excitement toward future machine learning projects. This has translated into a fantastic work environment, where there is an abundance of fresh fruit and coffee. I can work from home or in the office. I have flexible hours that allow me to work around my schedule, but the in-office perks make it hard to take full advantage of the remote work flexibility. Online advertising jobs in Data Science are very rewarding and I recommend this career for other Data driven people.

“Thank you so much for sharing your insights into a day in the life in Data Science at ExoClick!”

Conclusion: Data Science and Data Analytics career paths and opportunities

A day in the life in Data Analytics and Data Science are both challenging and rewarding. Working at ExoClick is a great opportunity as we have departments that interconnect with one another. If you are looking for Data Science and Data Analytics career paths and opportunities with company benefits like access to education, benefits, and a great work environment, check out our Careers Page! If you are an Advertiser or a Publisher who is looking for a reliable Ad Network that is dedicated to Data and innovation, contact us to see how ExoClick can help you achieve your Advertising goals today!