Fernando Reategui
Data AnalystAI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Data Scientist | Time Series Forecasting | NLP
I am a data scientist with experience developing models for time series forecasting, predictive maintenance, utilising classical statistical techniques and Machine Learning. Regarding tech stacks, I am proficient using the Python and R ecosystems. I also have working experience in NLP and Reinforcement Learning. I also have a background in wireless communications as a practitioner and researcher. I hold Master and PhD degrees from renowned universities through which I obtained a strong theoretical background in probability theory, information and communication theory and machine learning.
University of Surrey
PhD, Electronic Engineering (Information Theory)
January 1, 2010 – January 1, 2015
Karlsruhe Institute of Technology (KIT)
MSc, Electrical Engineering and Information Technologies
January 1, 2006 – January 1, 2009
Universidad Simón Bolívar
Bachelor, Electronic Engineering
January 1, 1995 – January 1, 2000
Sainsbury's
Data Scientist
January 1, 2026 – Present
MSD in the UK
Data Scientist
January 1, 2025 – October 1, 2025
London, United Kingdom
Haleon
Senior Data Scientist
June 1, 2022 – December 1, 2024
London, United Kingdom
UK Health Security Agency
Data Scientist
April 1, 2021 – May 1, 2022
London, United Kingdom · Remote
Self Employed
Independent Scientist
May 1, 2020 – December 1, 2020
RS Components
Senior Data Scientist
February 1, 2020 – May 1, 2020
London, United Kingdom · On-site
Atten2 Advanced Monitoring Technologies
Data Scientist
January 1, 2017 – December 1, 2019
London Area, United Kingdom · Remote
University of Surrey
PhD Student at the Institute for Communication Systems (ICS)
October 1, 2010 – February 1, 2015
Greater Guildford Area, United Kingdom
Karlsruhe Institute of Technology (KIT)
Master Thesis Student
July 1, 2008 – February 1, 2009
Karlsruhe, Baden-Württemberg, Germany
Siemens
Software Developer
December 1, 2006 – July 1, 2008
Karlsruhe, Germany · On-site
Siemens
Technical Sales Engineer
April 1, 2006 – September 1, 2006
Caracas, Venezuela · On-site
Huawei Technologies
Senior Wireless Engineer
November 1, 2005 – March 1, 2006
Caracas, Venezuela · On-site
Lucent Technologies
RF Engineer
September 1, 2000 – July 1, 2005
Caracas, Venezuela · On-site
TensorFlow in Practice Specialization
Coursera
June 24, 2026 – Present
Deep Learning Specialization
Coursera
June 24, 2026 – Present
edX Honor Code Certificate for The Analytics Edge
edX
June 24, 2026 – Present
Machine Learning
Coursera
June 24, 2026 – Present
AI for Medicine Specialization
Coursera
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has a strong academic background and diverse professional experience across multiple companies and sectors, including healthcare, retail, and manufacturing. This breadth of experience suggests adaptability and an ability to integrate into different organizational cultures. The transition from engineering roles to data science, and continuous learning through certifications, indicates a proactive and growth-oriented mindset. However, the target role is 'Data Analyst' while the candidate's experience is predominantly 'Data Scientist' and 'Senior Data Scientist', which might indicate a potential mismatch in role expectations or a desire for a more focused analytical role. The lack of specific project details makes it difficult to fully assess alignment with typical data analyst responsibilities.
Soft Skills & Operational Fit
The candidate's resume descriptions indicate experience in liaising with stakeholders, presenting work, and serving as a Subject Matter Expert, suggesting good communication and collaboration skills. The diverse project experience implies adaptability and problem-solving capabilities. However, without specific assessment data on soft skills or operational fit, a definitive conclusion cannot be drawn.