System Architect - Data and Machine Learning at Nokia
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Bringing expertise from Data Engineering and Machine Learning to develop cutting edge products. Big focus on leading and developing real-time, large-scale and scalable systems. Special interest in learning SOTA data and ML technologies and systems.
Aalto University
Master of Science - MS, Automation and Electrical Engineering
January 1, 2018 – January 1, 2020
Metropolia University of Applied Sciences
Bachelor of Engineering - BE, Electronics Engineering
January 1, 2014 – January 1, 2018
Nokia
System Architect (Data and ML) - RAN
January 1, 2023 – Present
Nokia
Software Engineer, Data and ML
June 1, 2019 – January 1, 2023
MDS Finland
Lead Engineer/ Project Manager - Machine Learning and Embedded Systems
June 1, 2018 – February 1, 2020
Helsinki Area, Finland
Talas Electric
R&D Electronics Engineer
July 1, 2017 – February 1, 2018
Helsinki Area, Finland
MDS Finland
Machine Learning Engineer, Life Sciences
May 1, 2017 – May 1, 2018
Helsinki Area, Finland
Cultural Fit Analysis
The candidate has a diverse background spanning telecommunications (Nokia), medical diagnostics (MDS Finland), and electronics R&D. Their roles have consistently involved leading technical initiatives, designing systems, and working with advanced data and ML technologies. This breadth of experience, coupled with a focus on data-driven solutions, aligns well with a dynamic, innovation-focused environment. The transition from System Architect to a Data Analyst role might require a shift in focus from system design to in-depth data interpretation and reporting, but the underlying technical skills are highly relevant.
Soft Skills & Operational Fit
The candidate's experience descriptions highlight leadership, project management, and involvement in designing system architectures, suggesting strong organizational and strategic thinking skills. The breadth of technologies and project types indicates adaptability and a proactive approach to problem-solving. However, without specific psychometric test results, a detailed assessment of work attitude, stress handling, and team collaboration is not possible.