Yulia Afletunova afletunova

About me

Hi, I’m Yulia. I have 7+ years of professional experience working across product ownership, analytics, and data platform engineering. I focus on designing and owning decision-making systems -- from metrics and experimentation frameworks to the data infrastructure behind high-stakes products.

I have worked in EdTech at Inquisitive (formerly MEL Science), FinTech at 3commas.io, and BigTech at Yandex.Search and most recently in an early-stage startup Emerge, building a privacy-first data platform. Throughout my career, I've developed expertise in Python, SQL (PostgreSQL), A/B testing, and product thinking.

Additionally, I founded the Russian-speaking community Analyst Girls Club for women in analytics, which encompasses data analytics as well as systems and business analytics. In my spare time, I mentor individuals looking to enter or advance in this field.

My interests bridge technical depth with interdisciplinary exploration. I like understanding how signals, systems, and minds create meaning.

Outside of work, I study Computational Neuroscience and Bioinformatics.

I am always interested in meeting new people and finding like-minded people in different fields. So feel free to drop me a message and get to know me, or ask questions if you think I can help.

Email me at: afletunova.yulia@gmail.com

Recent Work — Building a Privacy-First Data Platform

In the last six months, I architected and developed the company’s data platform using Python, dbt, Airflow, and ClickHouse. My contributions covered ingestion, transformations, storage, metadata, orchestration, and production stabilisation.

Core Skills

Data & Analytics: A/B testing design & evaluation, statistical analysis, hypothesis testing, product analytics, metrics selection, ETL development, data modelling
Engineering & Platform Work: Python, SQL (PostgreSQL, ClickHouse), dbt, Airflow, API design, ingestion pipelines
Visualisation & Communication: Plotly, Matplotlib, Seaborn, DataLens, Metabase, insight communication for technical & non-technical audiences, writing documentation, onboarding guides, and architectural explanations
Soft Skills: Research-oriented mindset, problem decomposition, systems thinking, mentoring, and knowledge sharing

Featured Projects (in progress)

Certifications

Neuromatch Academy certificate in computational neuroscience

Career Goals

Currently, my professional goals include:

Creating transparent and fair methods for using large-scale data responsibly.
Understanding how human minds work and how behaviour evolves, ideally quantified through data.
Expanding my expertise in computational neuroscience and bioinformatics to explore the intersection of data science and human health, especially mental health.

Long-term, I aim to:

Transition into a researcher role exploring data’s impact on mental health and genetics.
Build scalable frameworks for analytics, making it more accessible to everyone.
Mentor and support aspiring data analysts through educational initiatives.