Quick Bio

Hello there, my name is Nikos Maniatis and I currently work as a Data Scientist at Procter & Gamble, based in Geneva, Switzerland. Apart from that, I really enjoy listening to loud music, playing the electric guitar, brewing delicious coffee and picking up new exciting hobbies. Below, you can find a list of my education and experience.

Experience

• Data Scientist - Procter & Gamble

  (Jan. 2024 - current) | Geneva, Switzerland

  In this role, I specialize in LLM based internal-facing products such as RAG or conversational analytics (text2sql) systems. I lead the data science algorithmic development of a text2sql application, ensuring scalability and reliability for thousands of users and consistency of answers through comprehensive LLM evaluation.
  Collaborating with a diverse team of technical experts, I manage third-party contractors and develop solutions in collaboration with business partners across multiple business units. My work involves staying at the forefront of technological advancements, implementing best practices, and driving innovation to deliver value to the organization through increased employee productivity.

• Data Scientist in Oral Care - Procter & Gamble

  (Oct. 2022 - Dec. 2023) | Geneva, Switzerland

  As an oral care embedded data scientist, the main goal is to leverage modern data science methods to build scaled solutions that aim to optimize the work done in the Professional Oral Health programs. In this program, sales representatives visit dental professionals throughout Europe, so identifying their potential and optimizing the visit frequency and intensity are some of the tasks at hand.

• Data Analytics Intern - Procter & Gamble

  (Jan. 2022 - Oct. 2022) | Athens, Greece

  A 6-month internship that was later extended to 9 months, in the Analytics & Insights team of the Southeastern European P&G cluster. Projects involved in:

  • Price Elasticity: Developed a new automated capability calculating weekly the price elasticities for top P&G brands, for Greece and Romania, utilizing Trade Panel Data and a regression model. This capability saved a potential 10% of the team’s annual budget.

  • Efficient Assortment: Migrated an efficient assortment tool to the cloud, using Microsoft Azure, so that the reports are refreshed automatically. Also, incorporated new reports aiming to help store managers with the close proximity stores.

  • Value Alerts: Contributed in bringing a new capability to the market, in collaboration with the central European team. Developed an alert that identifies products that are out of stock in specific stores, helping the store managers in their store checks.

Education

• MSc Data Science & Machine Learning

  National Technical University of Athens | (2020 - 2022) | Athens, Greece

  Thesis: Self-Supervised Deep Learning Denoising on seismic data. Code available in GitHub.

• BSc Physics

  National Kapodistrian University of Athens | (2015 - 2019)) | Athens, Greece

  Thesis: Geant4 (C++) Simulations on DEGAS detectors. Code available in GitHub.