CV

Education

• Ph.D. (with Prof. Tom Fearn and Dr. Ioanna Manolopoulou), Department of Statistical Science, University College London (UCL), UK
  • Research and travel awards (Google/ISBA, UCL, IPEP)
• MSc Statistics & Mathematical Modelling, Department of Mathematics, Aristotle University of Thessaloniki (AUTH), Greece
  • Best paper award for young scientists - SMTDA 2012
  • Research and travel awards (AUTH, IPEP)
• 7th Summer School on Mathematics, University of Crete (UOC), Greece
  • Travel award (UOC)
• Erasmus studies, Department of Mathematics, University of Valencia, Spain
  • Travel award (State Scholarships Foundation (IKY))
• 6th Summer School on Mathematics, University of Crete, Greece
  • Travel award (UOC)
• BSc Department of Mathematics, Aristotle University of Thessaloniki, Greece
  • 3 awards for outstanding performance (State Scholarships Foundation (IKY))

Work Experience

• 09/2020 - Present, Raising IT, Data Scientist, London, United Kingdom

• 02/2020 - 09/2020, Wayhome, Data Scientist, London, United Kingdom

• 01/2017 - 01/2020, GSK, Principal Statistician / Data Scientist, CMC (non-clinical), Biostatistics, R&D, Ware, Greater London, United Kingdom.

  I provided high quality statistical support to scientists at different groups aiming to improve decision making at various steps during the design of new medicines (tablets or inhalers) for a couple of products, e.g., to treat HIV, Asthma, Anaemia associated with chronic kidney disease.

  • 5 awards for leading innovative and high quality analysis to improve quality of patient’s life

• 10/2013 - 12/2016, Teaching assistant, Department of Statistical Science, University College London, United Kingdom

• 02/2012 - 06/2012, Teaching assistant in Statistics, Department of Mathematics, Aristotle University of Thessaloniki, Greece

Volunteering

• Data Science Specialist, ASA Five College DataFest, Amherst, Massachusetts, USA, Two two-day data-science competitions (2014, 2015).
  • I was responsible for data-science tutoring and explaining Statistics and Machine Learning concepts to undergraduate students.

Technical Skills

• Programming:
  • Python (e.g., Pandas, NumPy, SciPy, Matplotlib, SciKit-Learn)
  • SQL, Google BigQuery
  • SAS (including High-Performance Computing (HPC))
  • R and Shiny app (including HPC)
  • MATLAB (including HPC)
  • Mathematica
• User Interface softwares:
  • Tableau
  • Statistica (Advanced analytics software)
  • Design-Expert (DX) (Design, analyse and optimise experiments)
  • SPSS
  • Minitab
• Operating systems:
  • Windows
  • Linux
  • Mac OS

Professional Membership

• Promoting Statistical Insight (PSI)

Former Member of

• Centre for Computational Statistics and Machine Learning (CSML)
• Network of Computational Statistics and Machine Learning (NCSML)