Jedrzej Kardach，波兰波兹纳斯的开发者
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Jedrzej Kardach

Verified Expert  in Engineering

数据科学家和机器学习开发人员

Location
Poznań, Poland
Toptal Member Since
May 22, 2023

Jedrzej是一位多才多艺的全栈数据科学家和ML工程师，拥有5年的经验. 具有较强的Python后端工程技能, he excels in fast-paced, 以客户价值为中心的工作环境. Jedrzej与普林斯顿大学ORFE部门合作开发了尖端的模拟环境，以构建赞助搜索拍卖算法. Additionally, 他已经成功地交付了多个基于nlp的分类算法和强化学习解决方案.

Data MiningMachine LearningLinear RegressionData InferenceData ScientistData AnalysisData AnalyticsData ModelingProgrammingClusteringArtificial Intelligence (AI)Natural Language Processing (NLP)MacOSPythonScikit-learnGoogle AdWordsSupport Vector MachineSimulationNoCodeAPI

Portfolio

Kalepa
算法，数据挖掘，决策树回归，数据结构...
Booksy
Python, Python 3, BigQuery, Google BigQuery, Pandas, NumPy, Matplotlib...
Ora Ai
算法，Python 3, Python, NumPy, Pandas, Scikit-learn, TensorFlow...

Experience

Python - 5 yearsSQL - 5 yearsData Science - 5 yearsMachine Learning - 5 yearsDeep Learning - 4 years人工智能(AI) - 4年REST - 2 years自然语言处理(NLP) - 2年

Availability

Part-time

Preferred Environment

MacOS, Jupyter Notebook, PyCharm, Python, Django, Machine Learning, Deep Learning, TensorFlow, Scikit-learn, Pandas

The most amazing...

...我所做的就是让一个比我高两级的专家创建的模型的性能提高了5倍.

Work Experience

Machine Learning Engineer

2022 - 2023
Kalepa
  • 提出了一个包含主题分类和命名实体识别的NLP二元分类模型, 取得了5倍的改进F1分数比前任, defined target variables, and supervised labeling efforts.
  • 推出多个多标签NLP分类模型，用于从大型非结构化文本数据中获取有关业务实体的见解.
  • 从大型非结构化文本数据构建了一个信息检索算法.
  • 维护模型的后端基础设施，并使用无服务器AWS Lambda进行部署, AWS Step Functions, and Amazon SageMaker.
  • 将ChatGPT API集成到公司的面向客户的服务中, 其中包括提示工程，以最大化ChatGPT在给定用例中的效用.
Technologies: 算法，数据挖掘，决策树回归，数据结构, Deep Learning, TensorFlow, Natural Language Toolkit (NLTK), Natural Language Processing (NLP), Python, Python 3, Amazon Web Services (AWS), AWS Lambda, AWS Step Functions, PostgreSQL, SQL, Machine Learning, Scikit-learn, NumPy, Pandas, Seaborn, Matplotlib, Hyperparameters, Random Forests, Support Vector Machines (SVM), Logistic Regression, Linear Regression, Web Scraping, Data Inference, ChatGPT, Amazon SageMaker, Git, GitHub, Jira, Confluence, Jupyter Notebook, ETL, Classification, Text Classification, Text Mining, APIs, Jupyter, Requests, Information Retrieval, Artificial Intelligence (AI), Data Science, Data Analysis, Data Analytics, Data Modeling, Data Visualization, Data Collection, OpenAI GPT-3 API, Language Models, Classification Algorithms, 生成预训练变压器(GPT), GPT, 生成预训练变压器3 (GPT-3), Pytest, Keras, Dashboards, Analytical Dashboards, Programming, Integration, OpenAI GPT-4 API, TensorFlow深度学习库(TFLearn), Modeling, Exploratory Data Analysis

Data Scientist

2020 - 2022
Booksy
  • 为应用程序的某些部分开发了基于事件的产品监控体系结构, 为A/B测试设计性能监控, 并建议对产品进行改进，从而使B2C收购增加30%.
  • 设计并实现ETL管道和机器学习模型，用于流失预测和用户聚类.
  • 使用Microsoft Power BI、SQL和BigQuery交付商业智能仪表板.
Technologies: Python, Python 3, BigQuery, Google BigQuery, Pandas, NumPy, Matplotlib, Scikit-learn, TensorFlow, ETL, Jira, Confluence, User Monitoring, Firebase, Microsoft Power BI, Business Intelligence (BI), Classification, Machine Learning, Google Cloud Platform (GCP), Support Vector Machines (SVM), Clustering, K-means Clustering, Logistic Regression, Linear Regression, Decision Trees, Random Forests, XGBoost, Artificial Intelligence (AI), Data Science, Data Scientist, Data Analysis, Data Analytics, Predictive Modeling, Predictive Analytics, Forecasting, Data Modeling, Data Visualization, Data Collection, Classification Algorithms, Keras, Dashboards, Analytical Dashboards, Interactive Dashboards, Programming, TensorFlow深度学习库(TFLearn), Modeling, Exploratory Data Analysis, Consumer Behavior

Data Scientist

2018 - 2022
Ora Ai
  • Conducted a yearlong R&与普林斯顿大学的运筹学和金融工程系合作, 专注于开发谷歌广告环境的模拟器，用于在强化学习环境中进行策略测试.
  • 构建了无数基于机器学习的模块来预测时间序列, 解决回归和分类问题, 或者特定度量的近似值. 所有这些模块都有助于主竞价算法做出最终的竞价建议.
  • 与普林斯顿大学的研究人员一起参与了人工智能技术的开发，以优化管理赞助搜索拍卖的竞标过程.
  • 合作开发一个酒店经济环境的模拟器，使用蒙特卡洛方法，允许测试自动营销的算法.
  • 共同开发用于酒店自动营销的强化学习算法. 这包括为特价产品设定最优价格，选择合适的沟通渠道和时间.
  • 共同创建了一个网络应用程序，促进了数字营销活动的监督，以及管理这些活动的人工智能.
  • 开发了Django REST API和ETL管道，用于从酒店管理软件中实时收集数据.
Technologies: 算法，Python 3, Python, NumPy, Pandas, Scikit-learn, TensorFlow, Ad Optimization, Optimization, Google Ads, Google AdWords, Real-time Bidding (RTB), Online Bidding, Simulations, Reinforcement Learning, Time Series, Linear Regression, Logistic Regression, Decision Trees, Random Forests, XGBoost, Support Vector Machines (SVM), Clustering, K-means Clustering, Django, Django ORM, Django REST Framework, REST, Postman, Docker, Docker Hub, Docker Cloud, Docker Compose, Amazon Web Services (AWS), Amazon EC2, Amazon S3 (AWS S3), PostgreSQL, MySQL, SQL, SQLite, SQLAlchemy, Dash, Web Dashboards, Dashboard Design, Plotly, Seaborn, Matplotlib, Flask, SciPy, Jira, Learning, Bayesian Statistics, Bayesian Inference & Modeling, Operations Research, Bitbucket, Git, Artificial Intelligence (AI), Data Science, Data Scientist, Data Analysis, Data Analytics, Predictive Modeling, Predictive Analytics, Forecasting, Data Modeling, Data Visualization, Data Collection, Classification Algorithms, Keras, Data-driven Marketing, Pricing Models, Dashboards, Analytical Dashboards, Interactive Dashboards, Programming, Modeling, Exploratory Data Analysis, Consumer Behavior

呼叫中心最优激励方案体系

http://www.cambridge.org/engage/miir/article-details/61831286ad7f7c742d5411f5
参与设计了一个大型呼叫中心员工的最佳任务分配系统，并发表了一篇论文. 这样做的目的是使员工的工作效率最大化，同时使他们的压力保持在可接受的水平.

Languages

Python, Python 3, SQL, Java

Libraries/APIs

Scikit-learn, Pandas, NumPy, Matplotlib, XGBoost, TensorFlow, Django ORM, SQLAlchemy, Keras, TensorFlow深度学习库(TFLearn), Natural Language Toolkit (NLTK), Google AdWords, SciPy, Requests

Tools

Seaborn, Jupyter, PyCharm, Git, GitHub, BigQuery, Postman, Bitbucket, AWS Step Functions, Amazon SageMaker, Jira, Confluence, Microsoft Power BI, Docker Hub, Docker Compose, Plotly, Pytest

Paradigms

数据科学，ETL，商业智能(BI)， REST，线性编程

Platforms

MacOS, Jupyter Notebook, Amazon Web Services (AWS), AWS Lambda, Firebase, Google Cloud Platform (GCP), Docker, Amazon EC2, NoCodeAPI

Other

Data Mining, Machine Learning, Natural Language Processing (NLP), Logistic Regression, Linear Regression, Data Inference, Classification, Text Classification, Text Mining, Simulations, Clustering, K-means Clustering, Learning, Artificial Intelligence (AI), Data Scientist, Data Analysis, Data Analytics, Predictive Modeling, Data Modeling, Classification Algorithms, Programming, Modeling, Algorithms, Random Forests, Support Vector Machines (SVM), Decision Trees, Gradient Boosted Trees, Time Series, Time Series Analysis, Data Structures, Deep Learning, Hyperparameters, Web Scraping, APIs, Google BigQuery, User Monitoring, Real-time Bidding (RTB), Online Bidding, Reinforcement Learning, Bayesian Statistics, Predictive Analytics, Forecasting, Data Visualization, OpenAI GPT-3 API, Language Models, GPT, 生成预训练变压器3 (GPT-3), Data-driven Marketing, Pricing Models, Dashboards, Analytical Dashboards, OpenAI GPT-4 API, Exploratory Data Analysis, Linear Algebra, Statistics, Statistical Methods, Probability Theory, Optimization, Partial Differential Equations, Finance, Mathematics, Analysis, Mathematical Analysis, Cryptography, Discrete Mathematics, Operations Research, Sorting Algorithms, Random Forest Regression, Support Vector Regression, Decision Tree Regression, ChatGPT, Ad Optimization, Google Ads, Dash, Web Dashboards, Dashboard Design, Bayesian Inference & Modeling, Information Retrieval, Data Collection, 生成预训练变压器(GPT), Interactive Dashboards, Integration, Consumer Behavior

Frameworks

Django, Django REST框架，Flask

Storage

PostgreSQL, MySQL, SQLite, Docker Cloud, Amazon S3 (AWS S3)

Industry Expertise

Project Management

2017 - 2018

Master's Degree in Mathematics

伦敦政治经济学院(LSE) -英国伦敦

2013 - 2017

Bachelor's Degree in Mathematics

伦敦国王学院——英国伦敦

AUGUST 2013 - PRESENT

Project Management Advanced Topics

Project Management Institute (PMI)

AUGUST 2013 - PRESENT

Project Management Fundamentals

Project Management Institute (PMI)

Collaboration That Works

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