Welcome to Spiess Solution
Hello, I’m Lukas Spiess, the driving force behind Spiess Solution. I grew up in the beautiful North Rhine-Westphalia in Germany, a place that nurtured my deep-seated curiosity and love for analysis. This led me to pursue studies in research psychology and cognitive neuroscience in the scenic Netherlands. More than an academic journey, this experience was a personal evolution, as the Netherlands gradually became my second home. Now, I’m happily settled here with my wife, enjoying the Dutch way of life, though I confess, for longer journeys, my German preference for walking or driving still wins over cycling!
At Spiess Solution, which I founded, I blend a practical approach with a belief in limitless possibilities in data science and solving challenges. With over 7 years of expertise in machine learning, AI, statistics, and analytics, I’ve improved my ability to not just interpret data but also to make it accessible and understandable to others. I love unraveling complex concepts, a skill that almost led me down the path of teaching, inspired by some family members. However, the fascinating realm of data captured my heart.
My academic background in psychology and cognitive neuroscience is the cornerstone of my emphasis on methodical, data-driven decision-making. After my PhD, I ventured into the dairy industry, developing innovative data-driven quality assurance methods. I then moved on to become a senior data science consultant at Valcon, where I worked on large-scale data solutions. These experiences have been pivotal in crafting my vision for Spiess Solution. My ambition with Spiess Solution is to be a trusted partner for small to medium-sized businesses, helping them harness data and technology to compete with larger counterparts.
If you’re eager to explore the potential of your data, I encourage you to get in touch with me at info@spiess-solution.com. Let’s collaborate to turn your data into tangible value for your business.
Programming
Python, SQL, R, Matlab
Machine Learning and Deep Learning frameworks
Tensorflow, PyTorch, Scikit-learn
Big Data and Cloud Platforms
Pyspark, Databricks, Azure stack
Data analysis and visualization
Pandas, numpy, scipy, plotly, Power BI
Development and Project Management
Git, CI/CD, Scrum, Agile
Languages
German, English, Dutch. All fluent
Consulting
I am a pragmatic problem-solver with over 3.5 years of experience in delivering business value. While always keeping the bigger picture in mind, I can also quickly and flexibly dive into the finest details when needed. This makes me an efficient and adaptable colleague within highly diverse teams but also equally capable of working independently. I have experience as a project lead and are proficient in translating complex topics for diverse stakeholders. When interacting with others, I focus on clarity and purpose while emphasizing honesty, care, and transparency. For me, delivering business value is more than delivering data solutions – it is about achieving and sustaining business impact.
Insights
With 7+ years of expertise in both academic and business settings, I excel in designing, conducting, analyzing, and extracting valuable insights from quantitative research, ranging from A/B tests to extensive validation studies. I have a profound understanding of inferential statistics, which empowers me to apply and interpret statistical models. This helps in discerning how and to what extent various factors influence a specific outcome. Moreover, I have industry experience with trend analyses, uncertainty assessments, cluster analyses, and the analysis of complex high-dimensional data. Additionally, I have experience in crafting tailored interactive data visualizations and dashboards to turn data into actionable insights.
AI
I possess a deep understanding of and expertise in various machine learning and AI algorithms, tailored for tasks such as predicting quantities, time series forecasting, product matching, anomaly detection, and categorization. Leveraging my strong statistical and mathematical foundation, I enjoy the challenge of designing practical yet impactful data-driven solutions. I prioritize rigorous testing and validation to ensure the robustness and fairness of AI implementations. Additionally, I am committed to making machine learning and AI solutions explainable: understanding an algorithm’s behavior is critical for ensuring quality, fostering trust, and encouraging adoption.
Career
2023 – present
Business Owner and Data Science Consultant
Spiess Solution
2022 – 2023
Senior Data Science Consultant
Valcon B.V.
2020 – 2022
Data Scientist and Project Lead
Qlip B.V.
2015 – 2020
Doctoral Researcher Social Cognitive Neuroscience
Donders Institute for Brain, Cognition, and Behavior
Radboud University Nijmegen
2015
Donders Institute: TopTalent Doctoral Research Grant
Awarded for designing an advanced 4-year research plan
in a highly competitive selection process.
Professional Development
2022
Academy Accreditation:
Databricks Lakehouse Fundamentals
2022
Microsoft Certified:
Azure Fundamentals
2021
Coursera:
Neural Networks and Deep Learning
2017
Coursera:
– People Analytics
– Operations Analytics
– Customer Analytics
Education
2013 – 2015
Research Master Cognitive Neuroscience (M.Sc.)
Distinction: Cum Laude
Radboud University Nijmegen
2011 – 2013
Honors Program Psychology
Honours Academy
Radboud University Nijmegen
2010 – 2013
Bachelor Psychology (B.Sc.)
Radboud University Nijmegen
Academic Publications
De Geus, Y., Scherpenisse, P., Smit, L.A.M., Bossers, A., Stegeman, J.A., Spiess, L., & Koop, G. (2023). Total Bacterial Count and Somatic Cell Count in Bulk and Individual Goat Milk around Kidding: Two Longitudinal Studies, in prep.
Rutar, D., Colizoli, O., Selen, L., Spiess, L., Kwisthout, J., & Hunnius, S. (2023) Differentiating between Bayesian parameter learning and structure learning based on behavioural and pupil measures. PLoS ONE 18(2): e0270619. https://doi.org/10.1371/journal.pone.0270619
Spiess, L., de Peinder, P., & van den Bijgaart, H. (2021). Advances in Atypical FT-IR Milk Screening: Combining Untargeted Spectra Screening and Cluster Algorithms. Foods (Basel, Switzerland), 10(5), 1111. https://doi.org/10.3390/foods10051111
Vacaru, S. V., van Schaik, J. E., Spiess, L., & Hunnius, S. (2021). No evidence for modulation of facial mimicry by attachment tendencies in adulthood: An EMG investigation. The Journal of Social Psychology. https://doi.org/10.1080/00224545.2021.1973946
Spiess, L., & Bekkering, H. (2020). Predicting choice behavior of group members. Frontiers in Psychology, 11. https://doi.org/10.3389/fpsyg.2020.00508
Spiess, L. (2020). Who are you and how many? The role of individual knowledge and group knowledge in social predictions [Doctoral dissertation, Radboud University]. [S.l.] : [S.n.]. (Original work published 2020). https://hdl.handle.net/2066/226306