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Mark NuisMN

Mark Nuis

Senior Data Scientist/Engineer

€ 800/dag
Amsterdam, NL
8-15 jaar

Gemiddelde responstijd: 1 uur

Over Mark

During my professional career of over 10 years and an educational background in Econometrics, I have gained experience in various fields with a focus mainly on Data Science, Data Engineering, Quantitative Trading, and Data Management.

Through my experience as an entrepreneur and freelancer, I have developed excellent communication and presentation skills, a strong sense of independence, and the ability to lead, mentor, and collaborate effectively with others. And by working in demanding environments at multiple trading firms, I have developed excellent time management skills and the ability to work under pressure.
  • Nederlands

    Tweetalig / moedertaal

  • Engels

    Vloeiend

Kan op locatie werken
Amsterdam (tot 50km), Rotterdam (tot 50km), Utrecht (tot 50km)

Werkervaring

  • ABN Amro Bank- Data Cleansing & Remediation
    Senior Data Engineer (Freelancer)
    BANKEN & VERZEKERINGEN
    september 2023 - september 2025 (2 jaren)
    Amsterdam, Nederland
    Created ETL pipelines to extract data from numerous sources within the bank and store in structured format within a DataVault solution using Azure Databricks and Azure Data Factory.

    Responsible for enhancing billions of transactions records for all clients used in Credit Risk model redevelopment and IFRS9 reporting every quarter.

    Contributed to the largest data migration within the bank to improve the credit
    proposal process and to capture high quality data on collateral management.

    Created automated data flows to and from consumers to enhance and enrich data attributes used for Credit Risk model redevelopment.

    Implemented automated data quality reports to run daily on incremental data
    before processing in ETL pipelines.
    Azure Databricks Cloud Azure Azure Data Factory Apache Spark ETL
  • Bunker Crypto Trading
    Head of Trading (Co-Founder)
    HIGHTECH
    maart 2022 - september 2023 (1 jaar en 6 maanden)
    Utrecht, Nederland
    Manages the full Azure stack such as: Kubernetes, Log-analytics, Load-Balancer, Storage accounts, Databricks, Container registry, NAT Gateway, Key Vaults and Managed Identities.

    Built complete automated CI/CD pipeline in Azure Devops with Docker to deploy and continuously update trading strategies on a Kubernetes server in Azure without downtime.

    Developed a fully automated market making software in Rust on Bitvavo, Binance and Bybit for spot and futures and automatically deployed on AWS bare metals.

    Built a FPGA solution to retrieve and parse market data on ultra-low latency
    deployed in AWS.

    Developed a new scalable pair trading strategy that targets an annual unleveraged return of 30% using statistical/econometric models.

    Using PySpark in Azure Databricks to process and store 100 billion records daily.

    Train random forest models on multiple terrabytes of orderbook data to predict certain events.

    Designed a backtesting framework in Databricks that greatly speeds up the research of new strategies and reduces the time to bring them in production.

    Developed a new momentum strategy using a Neural Network to process real-time news messages.
    Azure DevOps PySpark Rust Machine Learning & AI Azure & AWS
  • Webb Traders
    Senior Quantitative Trader
    HIGHTECH
    februari 2020 - februari 2022 (2 jaren)
    Amsterdam, Nederland
    Making markets in all European index options and single stock options.

    Operating and monitoring automated trading strategies.

    Responsible for the daily PNL and overall monitoring of risk exposures.

    Utilizing a variety of econometric/statistical models and machine learning models to develop new trading strategies or to enhance existing ones.

    Research, analyse and backtest the new trading ideas on both stock and index
    futures using tick data and in-house cloud computing backtest software (Google Cloud Platform) in Python using Spark distributed computing.

    Implementing non-latency dependent trading strategies in production environment in Python.

    Liaising with developers to convert the latency dependent strategy developed in Python backtest to C++ production code.

    Liaising with risk and compliance to ensure our automated strategies trade within Webb Trader's risk profile and comply with all rules and regulations regarding automated trading.

    Developed and generate daily automated trade reports to improve and analyse the performance of the strategies based on the trades.
    Google Cloud Platform (GCP) Databricks Python Machine learning Econometrics

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Opleidingen

  • MSc
    Erasmus University Rotterdam
    2018
    MSc
  • BSc
    Erasmus University Rotterdam
    2016
    BSc

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