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Nick Settje

Data Scientist

Can work in or around Amsterdam

  • 52.3727
  • 4.8936
  • Suggested rate €700 / day
  • Experience 2-7 years
Propose a project The project will begin once you accept Nick's quote.

This freelancer is available full-time but hasn't confirmed their availability in over 7 days.

Propose a project The project will begin once you accept Nick's quote.

Location and workplace preferences

Amsterdam, Nederland
Can work onsite in your office in
  • around Amsterdam and 10km


Project length
  • Between 1-3 months
  • Between 3-6 months
  • ≥ 6 months
Business sector
  • Digital & IT
  • E-commerce
  • Internet of Things (IoT)
  • Logistics & Supply Chain
  • Research
+6 autres
Company size
  • 11 - 49 people
  • 50 - 249 people
  • 250 - 999 people
  • 1000 - 4999 people
  • ≥ 5000 people


Freelancer code of conduct signed
Read the Malt code of conduct

Verified email


  • English

    Native or bilingual


Skills (35)

Nick in a few words

My top goal is ROI for your investment in me. I have consistently been a top performer on every project I have done, and I aim to be one for you too.

Offering freelance consulting for: writing code and developing strategy for business intelligence, data science, machine learning, and predictive analytics.

This includes time series analysis, operations research, recommendation engines, text mining, computer vision, neural networks, cloud infrastructure automation, DevOps, MLOps, and more. I also have strong experience managing remote teams and driving product vision for companies with very large budgets.

​I have been writing code to analyze data and solve modeling problems for more than 10 years. I have also been a founding member of analytics teams in Asia and the US, working with multi-million-dollar budgets from startups to the Fortune 500.

I am an alumnus of Cornell and Stanford.


Decode Data Science

Lead Data Scientist

Amsterdam, North Holland, Netherlands

June 2021 - Today (1 year and 8 months)

- Freelance consulting for data science, AI, MLOps, and technical team development - Extensive technical experience with cutting edge technologies, including model building in Python/C, big data engineering with Spark, cloud automation via Terraform and AWS - Strong experience leading product vision for remote technical teams working with seven-figure budgets

State Farm ®

Senior Machine Learning Engineer

Bloomington, Illinois, United States

April 2021 - June 2021 (2 months)

- Successfully developed custom tools and frameworks for the complete MLOps lifecycle for models that manage ten figures of value for the largest auto insurer in the US - Focused on improving transparency in the modeling lifecycle, from data lineages to model correctness to automated model monitoring and event-based retraining - Worked mainly with Python, Docker, Terraform, AWS SageMaker, and GitLab CI/CD - Served as product owner for model monitoring, managing product vision and execution timelines for multiple technical products with a team distributed across 5+ locations in the US - Regularly advised on every part of the model lifecycle, including big data engineering, algorithmic model building, DevOps and high-availability, and ongoing model correctness

State Farm ®

Machine Learning Engineer

Bloomington, Illinois, United States

October 2019 - April 2021 (1 year and 6 months)

Forward Loop

Co-Founder, Director of Technology

Hong Kong

January 2018 - October 2019 (1 year and 9 months)

Infrastructure, software, applications, and hardware for IoT. Designed and built custom IoT products for manufacturing, retail, and other industries to improve how they use their business data.

Data Scientist

Hong Kong

September 2017 - December 2017 (3 months)

Gobee was a bike sharing company in Asia and Europe. Reported directly to the CEO and CTO to understand KPIs and business metrics in order to improve transparency of reporting and milestones. Advised on key metrics such as user acquisition, ROI on physical assets, and operation team efficiency. Worked closely with Gobee operations to improve geolocation accuracy for bikes, increase efficiency of regular on-the-ground maintenance routines, and expose near real-time maps to support all daily operations in four countries on two continents. Assumed direct responsibility for measurable improvements in the number of bikes that were located and serviced on a regular basis. Leveraged several technologies at Gobee, including Python (pandas, Numpy, scikit-learn, Flask), Microsoft Power BI, Jupyter Notebooks (Python), SQL, Node.js, Trello API, Zendesk API, and a private fork of with improved heatmap functionality.

Vectr Ventures

Data Analyst

Hong Kong

April 2016 - September 2017 (1 year and 5 months)

Vectr is a venture capital firm in Hong Kong. Designed and built custom big data and machine learning products to help portfolio companies leverage their data and automate their key business processes. Advised the investment team on how to assess technology companies in the machine learning, AI, big data, and blockchain sectors.

Stanford University

Graduate Student

January 2013 - January 2015 (2 years)

Successfully designed and implemented new algorithms to find solutions to quantum mechanical problems previously thought to be intractable. In addition to research, managed research group hybrid CPU/GPU supercomputer with more than one hundred nodes. In the course of study, completed extensive coursework in machine learning, compressed sensing, and convex optimization.

Cornell University

Undergraduate Research Assistant

January 2010 - January 2013 (3 years)

Nick developed an effective procedure for generating and analyzing large data sets using custom scripts integrating C++, bash, and molecular modeling software (written in Perl). He published his research work in a high impact factor journal as lead undergraduate for a five-member team: Lee, S., Henderson, R., Kaminsky, C., Nelson, Z., Nguyen, J., Settje, N. F., Feng, J. (2013). “Pseudo‐Fivefold Diffraction Symmetries in Tetrahedral Packing.” Chemistry-A European Journal, 19(31), 10244-10270.

Memorial University of Newfoundland

Research Assistant

June 2012 - August 2012 (2 months)

Nick studied novel polymers for use in measuring groundwater contamination in pristine water sources. He performed chemical experiments and analysis involving molecularly imprinted polymers (MIP), high performance liquid chromatography (HPLC), and gas chromatography (GC). His preliminary results showed a preparation of MIPs for sensitive measurement of caffeine and nicotine contamination in water that improved significantly on the industry standard.