Kategorie: Digital Strategy

Transition from Academia to Capgemini: A New Chapter in Data and Analytics

CERN Main Auditorium: my transition from academia to Capgemini
CERN Main Auditorium: my transition from academia to Capgemini

After enjoying research for the last four years, especially during my time at CERN, I have made a significant decision. I have decided to resign from my postgraduate position and make a transition from academia to the exciting world of Capgemini. My passion for Data and Analytics remains strong and will be the core focus of my new role.

Capgemini: A New Adventure After Academia

Capgemini, one of the world’s largest consulting corporations, has caught my attention. Unlike many other consulting companies, Capgemini does not yet have a dedicated team to offer effective strategies and solutions employing Big Data, Analytics, and Machine Learning. This presents an exciting opportunity for me to contribute and innovate.

My Vision: Building a Data-Driven Future at Capgemini

I love these technologies and am confident in my ability to elaborate a business development plan to drive business growth. Through customer and market definition, my plan includes new services such as:

  • Data Science Strategy: Enabling organizations to solve problems with insights from analytics.
  • Consulting: Answering questions using data.
  • Development: Building custom tools like interactive dashboards, pipelines, customized Hadoop setup, and data prep scripts.
  • Training: Offering various skill levels of training, from basic dashboard design to deep dives in R, Python, and D3.js.

This plan also includes a go-to-market strategy, which I’ll keep under wraps for now. Stay tuned for a retrospective reveal in the future!

Reflecting on My Transition from Academia

Making this transition from academia to a corporate role has been a considered decision. As I previously shared in my reflection on my software engineering internship at SAP, the blend of technological challenges and team collaboration has always intrigued me. Joining Capgemini allows me to continue pursuing my passion for data in a dynamic business environment.

Conclusion: Exciting Times Ahead

This transition from academia to Capgemini marks a thrilling new chapter in my career. I look forward to leveraging my expertise in Data and Analytics to contribute to Capgemini’s growth and innovation.

Follow my journey as I explore the intersection of data, technology, and business. Connect with me on Twitter and LinkedIn.

Data Science Research: Unlocking the Secrets of the Universe with Big Data at CERN

Time really flies when you immerse yourself in the world of data science research and unravel the mysteries of the universe! It’s been an incredible journey over the past year as I’ve immersed myself in the world of data science at CERN. For those unfamiliar, CERN — set against a stunning backdrop of snow-capped mountains and tranquil Lake Geneva — is home to the Large Hadron Collider (LHC), the world’s most powerful particle accelerator. But what often goes unnoticed is the critical role that data science plays in powering this colossal machine and its quest for groundbreaking discoveries like the elusive Higgs boson.

The Data Tsunami: A Behind-The-Scenes Look

Imagine having to sift through one petabyte (PB) of data every second — yes, you read that right. That’s the amount of data generated by the LHC’s detectors. To make it manageable, high-level triggers act as an advanced filtering system, reducing this torrent of data to a more digestible gigabyte per second. This filtered data then finds its way to the LHC Computing Grid.

High-Level Trigger data flow, crucial for data science research in the ALICE experiment at CERN.
High-Level Trigger data flow, crucial for data science research in the ALICE experiment at CERN.

About 50PB of this data is stored on tape, and another 20PB is stored on disk, managed by a Hadoop-based cloud service. This platform runs up to two million tasks per day, making it a beehive of computational activity.

The Role of Data Science Research at CERN

Data scientists and software engineers are the unsung heroes at CERN, ensuring the smooth operation of the LHC and subsequent data analysis. Machine learning algorithms are used to discover new correlations between variables, including both LHC data and external data sets. This is critical for real-time analysis, where speed and accuracy are of the essence.

While managing the exponential growth of data is an ongoing challenge, the role of data scientists at CERN goes far beyond that. We are at the forefront of fostering a data-driven culture within the organization, transferring knowledge, and implementing best practices. In addition, as technology continues to evolve, part of our role is to identify and integrate new, cutting-edge tools that meet our specific data analysis needs.

The Road Ahead: A Data-Driven Journey

Looking ahead, scalability will remain a key focus as CERN’s data continues to grow. But the horizon of possibilities is vast. From exploring quantum computing to implementing advanced AI models, the role of data science in accelerating CERN’s research goals will only grow.

As I celebrate my one-year anniversary at CERN, I’m filled with gratitude and awe for what has been an incredible journey. From delving into petabytes of data to pushing the boundaries of machine learning in research, it’s been a year of immense learning and contribution.

For more insights into the fascinating universe of CERN and the role data science plays in it, be sure to follow me on Twitter for regular CERN updates and data science insights: