I am currently in career transition from applied research to Data Science. Cross-validated is my personal blog to keep track of my projects and different HOWTOs related to Data Science and tech.

My background is hybrid – I am passionate about numbers and analytics, but also have management and consulting experience.

I am looking for job opportunities where I can help companies optimize marketing and product development by delivering actionable data insights using Python, SQL and Tableau (or similar technologies).

Feel free to contact me if you find my blog useful, think I might be a good fit or simply would like to connect.

My Background

I was born and grew up in Ukraine and lived in Germany for almost 10 years. Since 2018 I live in California, the US.

I have a PhD in Political Science (2017) and developed strong analytical, communication and management skills throughout my almost 10 years career in Applied Policy Research in Germany.

I have published over 40 analytical articles and gave over 30 public talks and lectures (see the full list under Achievements). So I know how to communicate results to different audiences. I also consulted and provided expertise on Ukrainian politics to German media, interested public and other stakeholders.

For almost 5 years I worked in a similar to a Product Manager role in academic setting - I was a Managing Editor of online analytical digest “Ukraine-Analysen” (3500+ subscribers) with two weeks publication deadlines.

In this role, I wore many hats:

  • Strategic Planning - defined the strategic direction of the digest based on our mission, in response to hot topics, subscriber’s interests, technological and financial resources available; built editorial calender
  • Collaborate & Coordinate - built relationships with potential authors/researchers worldwide (lead generation); coordinated the processes of proofreading, translation and layout
  • Day-to-day Management - implemented a content strategy: contacted authors, enforced deadlines and budget requirements, ensured quality and style compliance
  • Write & Edit - wrote a number of analytical articles myself and edited authors’ submissions when necessary
  • Data Visualizations & Asset Creation - collected, analyzed and visualized data on key topics of each issue (opinion polls, reviews of press coverage, statistical data, etc.).
  • Digital Analytics - monitored the key metrics (Click-through-Rates, Open Rates, Bounce Rates, Pageviews, Unsubscribes, etc) on a regular basis
  • Marketing Online and Offline - increased digest’s awareness at different public events where I was invited as a speaker; responsible for social media posts and website updates


As a Managing Editor, I developed high-impact content of 60+ issues. I am proud to say that digest’s subscription base grew by 35% under my management or over 1,000 extra highly-engaging subscribers.

I managed the digest during the critical time of increased international attention to Ukraine - the so called Ukrainian Crisis (Euromaidan Revolution, Annexation of Crimea, War in Donbass). “Ukraine-Analysen” provided unbiased analysis of the evolving events free of charge and was read by high-level decision makers in Germany.

Why Data Science?

As an undergrad in International Information, a unique program that combined courses in social sciences and data analysis (Excel, data visualization and statistics), I dreamed about predicting the future social events using past data - a naive, very broad and basically impossible objective - almost a decade before all the hype around data science. However, the techniques I learned in mid-2000s were rather basic and mostly explorative, so not that predictive after all.

When I enrolled in my PhD, I wanted to make use of more advanced methods. In 2013 I got first experience in natural language processing (NLP) using data science platform RapidMinder and began learning R. I also attended quantitative methods and Statistics courses at my university. Yet these methods didn’t find way into my final version of the thesis. As it is often in life, unexpected happened.

I took up a role of Managing Editor just before the Ukrainian Crisis. Due to a demanding job, I had to make adjustments to my PhD in order to finish it. As a result, the research methods I used are mainly qualitative. But I still have the urge to be more quantitative, partly due to unfinished projects from my PhD life, partly because I feel it fits better my personality.

So when the opportunity turned up and I moved to California for family reasons, I decided to fulfill my dream and become a Data Scientist.

My Data Science Skills

For one and half years I have studied full time online and made a portfolio of Machine Learning and Predictive Analytics projects using Python (Jupyter Notebooks, Visual Studio Code), SQL, Tableau, Excel.

Having a broad background allows me to learn quickly and I like to learn. See my completed Specializations and Nanodegrees on Certificates page.

Through online learning, I acquired experience in:

  • Cleaning and transforming data with Python libraries (Pandas, Numpy, Scikit-learn)
  • Data Preprocessing (One-Hot Encoding, Feature Scaling, Dealing with Missing Values, Dimensionality Reduction with PCA)
  • Data Visualizations and Explorative Data Analysis (EDA) using Matplotlib, Seaborn
  • Feature Engineering and selection
  • Training Machine Learning models using best practices (including train/val/test splits, class balance, outlier detection/removal)
  • Hyperparameters tuning (including GridSearchCV)
  • Setting up ML pipelines
  • Working with SQL databases


Python (Pandas, Numpy, Sklearn), Data Cleaning, Data Visualization (Matplotlib, Seaborn), SQL, Command Line, Git and Version Control, Machine Learning (Linear Regression, Classification, Clustering etc.), Probability/Statistics, Deep Learning, PyTorch, Keras.

I am ready to apply my Data Science skills to solve Marketing, Sales or Product problems either full-time, contract, remote or freelance.


I read a lot of non-fiction on a wide range of topics, like traveling, hiking and jogging.