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Jedrzej Kardach
Poznan, Poland
Enthusiastic, all-in-one data scientist experienced in building machine learning models from scratch based on custom made simulation environments. Familiar with sophisticated data analysis and visualisation I am currently exploring a new area - growth hacking. I am open to any data science roles and junior software engineer roles as this is a direction in which I currently try to develop in my free time.
CodersRank Score
What is this?
This represents your current experience. It calculates by analyzing your connected repositories. By measuring your skills by your code, we are creating the ranking, so you can know how good are you comparing to another developers and what you have to improve to be better
Information on how to increase score and ranking details you can find in this blog post.
60.2
CodersRank Rank
Top 6%
Based on:
9 events
Highest experience points: 0 points,
0 activities in the last year
Python
13.3
exp.
HTML
13.1
exp.
SCSS
6.2
exp.
Less
6.2
exp.
Stylus
6.2
exp.
CSS
6.2
exp.
JSON
3.5
exp.
Dart
5.3
exp.
List your work history, including any contracts or internships
Booksy
Nov 2020 - Jan 2021 (2 months)
Growth Analyst
Analyst for growth team. Mainly working with postgresql and python(pandas, seaborn) to analyse and visualize data
ORA AI
Sep 2018 - Jan 2021 (2 years 4 months)
Data Scientist
Co-developed AI technology that optimally manages bidding process in sponsored search auctions.
Constructed countless Machine Learning based modules that forecast time series, solve regression and classification problems or approximate values of certain metrics. All these modules aid main bidding algorithm in making final bid recommendations.
Conducted a year long full R&D process along with Operations Research and Financial Engineering department at Princeton University which focused on developing optimal decision making policies for sponsored search auctions problem. For this purpose a multi-agent Google Ads simulation environment was developed.
Co-developed web application facilitating supervision of digital marketing campaigns as well as AI that manages these campaigns.
Co-developed backend infrastructure that manages communication between AI system and Google Ads.
Constructed automated pipelines allowing deployment of various systems run by the company to AWS.
Constructed scripts (SQL and SQLAlchemy) that allow efficient data retrieval from / upload to relational databases.
Co-developed applications for NCBiR funding. I was mainly responsible for writing parts about planned R&D process and competitive landscape.
Constructed countless Machine Learning based modules that forecast time series, solve regression and classification problems or approximate values of certain metrics. All these modules aid main bidding algorithm in making final bid recommendations.
Conducted a year long full R&D process along with Operations Research and Financial Engineering department at Princeton University which focused on developing optimal decision making policies for sponsored search auctions problem. For this purpose a multi-agent Google Ads simulation environment was developed.
Co-developed web application facilitating supervision of digital marketing campaigns as well as AI that manages these campaigns.
Co-developed backend infrastructure that manages communication between AI system and Google Ads.
Constructed automated pipelines allowing deployment of various systems run by the company to AWS.
Constructed scripts (SQL and SQLAlchemy) that allow efficient data retrieval from / upload to relational databases.
Co-developed applications for NCBiR funding. I was mainly responsible for writing parts about planned R&D process and competitive landscape.
This section lets you add any degrees or diplomas you have earned.
London Shool of Economics
Masters, Applicable Mathematics
Sep 2017 - Sep 2018