Timo Klock，德国汉堡的开发者
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Timo Klock

Verified Expert  in Engineering

Machine Learning Developer

Location
Hamburg, Germany
Toptal Member Since
September 13, 2021

Timo is a full-stack data scientist with eight years of professional experience in data-heavy applications and a PhD in machine learning and statistics. 他可以作为数据工程师在工业应用程序的数据生命周期中担任不同的角色, data scientist, ML engineer, or data analyst. Timo在Python和SQL以及许多现代数据框架方面经验丰富.

Machine LearningStatisticsClusteringData InferenceStatistical LearningScikit-learnNumPyJSONSciPyData AnalysisDeep LearningData Analytics人工智能(AI)Data EngineeringMathematical ModelingStreamlitAirbyteApache ClickPyMongo

Portfolio

Legal Tech Scaleup
数据科学，机器学习操作(MLOps)， Python, SQL，雪花...
房地产分析平台
数据科学，Python，数据工程，SQL, Apache气流...
Simula Consulting
数据科学，数据分析，数据工程，优化，OptaPlanner...

Experience

Data Science - 7 yearsPython - 7 yearsMachine Learning - 6 years关系数据库服务(RDS) - 3年Cloud - 3 yearsDocker - 3 yearsData Engineering - 3 yearsSQL - 2 years

Availability

Part-time

Preferred Environment

Python, Machine Learning, Operations Research, Applied Mathematics, Cloud, Containers, Relational Databases, SQL, Warehouses, 机器学习操作(MLOps)

The most amazing...

...project I have contributed to was to build up a commercial real estate analytics data platform for a small startup from scratch.

Work Experience

数据科学家，机器学习工程师

2023 - PRESENT
Legal Tech Scaleup
  • 开发了一种数据驱动的领先评分算法，用于对即将提交的法律案件的质量进行分类.
  • Conceptualized and developed extendable MLOps infrastructure that streamlines the development and maintenance of ML models using open-source software (OSS) and serverless infrastructure in GCP.
  • Developed a data-driven model for scoring ongoing law cases with increasingly better data coverage.
  • Informed stakeholders in biweekly meetings about the importance of setting up an MLOps infrastructure if ML is planned to be used more heavily in the company.
  • 就与客户一般数据基础设施相关的问题进行咨询, 比如提高数据质量和数据覆盖率.
Technologies: 数据科学，机器学习操作(MLOps)， Python, SQL，雪花, Prefect, MLflow, HyperOpt, Scikit-learn, Pandas, NumPy, XGBoost, AutoML, Google Cloud Platform (GCP), Google Cloud

Data Platform Engineer

2021 - PRESENT
房地产分析平台
  • Developed a cloud-based data platform on Google Cloud Platform (GCP) that fuels a commercial real estate analytics platform covering the Norwegian market.
  • Researched data sources with the product team to conceptualize and develop new features for the analytics application.
  • 从提取中实现数据管道, including web scraping, API connections, 数据转储导入使用DBT转换web应用程序的数据.
  • Set up and maintained a self-hosted Airflow infrastructure to schedule data pipelines and various workflows.
  • Delivered customized data sets for clients using the analytics application and made the data accessible through Streamlit applications.
  • 使用Python的FastAPI框架实现和维护一个API, 为web应用程序开发人员提供无缝数据交付.
Technologies: 数据科学，Python，数据工程，SQL, Apache气流, Data Build Tool (dbt), Airbyte, ETL, ELT, Streamlit, FastAPI, REST, Google Cloud Platform (GCP), PostgreSQL, Elasticsearch, BigQuery, Docker Compose, Poetry, GitHub, Continuous Deployment, Continuous Integration (CI)

数据科学家，数据工程师

2020 - 2021
Simula Consulting
  • 在多个与数据科学相关的项目中担任技术顾问, machine learning, and optimization.
  • Developed the data science back end of the Norwegian COVID-19 tracking app Smittestopp for identifying contacts between potentially infected individuals based on Bluetooth and GPS data.
  • Served as a data engineer and analyst for a biotech company involved in discovering new drugs for aggressive forms of bile duct cancer.
  • Led a small team of developers to conceptualize and implement a large-scale solver for vehicle routing problems with several business constraints, 哪些是由公司的主要利益相关者定义的.
Technologies: 数据科学，数据分析，数据工程，优化，OptaPlanner, OR-Tools, Azure, Applied Mathematics, Python, Pandas, NumPy, Matplotlib, Dash, Plotly, GitHub, SQL, Predictive Modeling

Postdoc and PhD Student

2016 - 2021
Simula Research Laboratory
  • Wrote 10+ articles contributing to the fundamental understanding of commonly used methods in data science, machine learning, and AI. 论文均发表在国际知名期刊和会议上.
  • 撰写关于新的元启发式优化方法的文章，例如基于共识的优化.
  • 与圣地亚哥大学的顶尖研究人员建立了国际合作关系, Munich, Oslo, Genoa, and London.
  • Co-supervised the research interns and PhD students working on data science and machine learning projects.
  • 组织专题讨论会、讲习班、暑期学校和会议.
  • 在暑期学校和研讨会上教授机器学习方法的课程.
  • 向国际技术和非技术观众展示研究成果.
  • Conducted long-term research visits to data science and math departments at the Technical University of Munich, 巴尔的摩的约翰霍普金斯大学, 以及加州大学圣地亚哥分校.
技术:应用数学, Python, Data Science, Machine Learning, 人工智能(AI), Optimization, Metaheuristics, Pandas, Matplotlib, NumPy, Plotly, SciPy, Scikit-learn, Scikit-image, CVXOPT, Statistics, TensorFlow, PyTorch, Keras, Dimensionality Reduction, Clustering, Regression, Classification, Predictive Modeling

访问博士后学者

2019 - 2020
加州大学圣地亚哥分校
  • Contributed to the fundamental understanding of generative models and deep neural networks in the Department of Mathematics at UCSD.
  • 建立UCSD与奥斯陆Simula研究实验室之间的联系.
  • 共同撰写科学论文，并向更广泛的受众传播研究成果.
技术:应用数学, Python, Data Science, Machine Learning, 人工智能(AI), Optimization, Metaheuristics, Pandas, Matplotlib, NumPy, Plotly, SciPy, Scikit-learn, Statistics, TensorFlow, PyTorch, Keras, Regression, Classification

Intern and Student Trainee

2015 - 2016
OHB System AG
  • Acted as a full-time intern for six months and spent the next six months as a part-time student trainee in the systems engineering department of a spacecraft manufacturer OHB System.
  • Developed a mathematical model for microforce emissions from reaction wheels on in-orbit satellites.
  • Performed data analysis, modeling, and visualization for a comprehensive study about forces emitted by reaction wheels of in-orbit satellites.
  • 利用研究数据建立数学模型.
  • 共同撰写了一篇关于管理微振动对卫星性能影响的科学论文, 描述研究结果和开发的模型.
技术:MATLAB，数学建模，数据分析

Student Research Assistant

2011 - 2016
University of Bremen
  • Developed mathematical simulations of physical processes such as heat diffusion and stress and strain simulations.
  • Implemented a C++ toolbox for solving the level set equation (transport equation) with mass conservation and interface re-initialization.
  • Integrated level-set methods into two-phase heat equation solver based on extended finite elements and the FEniCS software framework.
  • Co-authored conference presentations and technical reports about level-set methods and solving multi-phase heat equations.
Technologies: MATLAB, ParaView, Mathematical Modeling, 偏微分方程, Applied Mathematics, Git, GitHub, Python

国家电晕跟踪应用程序的数据分析后端

This project aimed at developing a mobile Corona Tracking App to limit the spread of the COVID-19 disease within Norway. 它由挪威卫生部发布，由一个信息技术公司财团执行. 我是数据科学后端开发团队的一员, where we conceptualized and implemented contact identification algorithms based on Bluetooth and GPS data. 由于形势的紧迫性，开发环境非常敏捷. 该项目的主要挑战之一是设计一个高效的关系数据库, which allows for quickly querying necessary contact data between individuals to cope with high computational demand in times of high infection rates. Other challenges included data security due to the sensitivity of the data and dealing with uncertainty connected to Bluetooth and GPS data.

药物发现分析数据分析师

This project aimed to discover novel personalized drug combinations for the treatment of aggressive types of specific cancers. My responsibilities were to develop a data pipeline that integrates data from several pilot studies into a single database (ETL and wrangling), 验证不同研究间数据的一致性, 并根据常用的药物相互作用模型确定最有希望的药物组合. Moreover, 我把结果告诉了公司的主要利益相关者, 为此，我使用Python Dash和Plotly框架开发了一个交互式仪表板.

面向物流规模化的车辆路径优化

The project aimed at conceptualizing and implementing a large-scale vehicle routing solver subject to several business constraints. 我领导着一个由3名开发者组成的团队, 负责将涉众需求转化为可操作的代码, 统筹发展进程, 并与公司的利益相关者沟通进展和结果. The developed algorithm was based on the OptaPlanner software framework and metaheuristic optimization methods. It allowed solving problems with several thousands of instances within 1-2 hours of computational time on a standard laptop. We further used partitioning, multi-processing, and clustering techniques to increase the efficiency of the solver and benefit from running on larger clusters.
2016 - 2020

信息学与应用数学博士

奥斯陆大学-奥斯陆，挪威

2010 - 2016

计算数学硕士学位

不莱梅大学-不莱梅，德国

AUGUST 2021 - PRESENT

DP-900: Microsoft Azure数据基础

Microsoft

JUNE 2021 - PRESENT

Apache Spark (TM) SQL for Data Analysts

Coursera

MAY 2021 - PRESENT

深度学习专业化

Coursera

MAY 2016 - PRESENT

Machine Learning

Coursera

Libraries/APIs

Scikit-learn, NumPy, SciPy, Pandas, TensorFlow, Matplotlib, Keras, PyTorch, Flask-RESTful, PyMongo, PySpark, Kepler.gl, XGBoost

Tools

MATLAB, Scikit-image, Plotly, GitHub, Git, OptaPlanner, ParaView, Pytest, Jira, Gradle, Jekyll, Azure App Service, Spark SQL, Apache Airflow, BigQuery, Docker Compose, AutoML

Paradigms

Data Science, 面向对象编程(OOP), Object-oriented Design (OOD), ETL, 测试驱动开发(TDD), REST, Continuous Deployment, Continuous Integration (CI)

Languages

Python, XML, YAML, SQL, R, Kotlin, HTML, CSS, Snowflake

Storage

JSON, Azure Cosmos DB, NoSQL, MongoDB, Relational Databases, PostgreSQL, Elasticsearch, Google Cloud

Frameworks

Flask, Bootstrap, Apache Spark, JUnit, Streamlit

Platforms

谷歌云平台(GCP)， Docker, Azure, Azure PaaS, Databricks, Airbyte

Other

Applied Mathematics, Predictive Modeling, Machine Learning, Statistics, Dimensionality Reduction, Clustering, Regression, Classification, Data Inference, Statistical Learning, Optimization, 人工智能(AI), Data Analysis, Data Engineering, Dash, Metaheuristics, CVXOPT, Mathematical Modeling, 偏微分方程, Data Modeling, Deep Learning, Data Analytics, Cloud, 关系数据库服务(RDS), OR-Tools, 自然语言处理(NLP), Computer Vision, OpenStreetMap, Operations Research, GPT, 生成预训练变压器(GPT), Containers, Warehouses, 机器学习操作(MLOps), Data Build Tool (dbt), ELT, FastAPI, Poetry, Prefect, MLflow, HyperOpt

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