Available for new opportunities

Farrux Asrorqulov

Transforming complex data into actionable business decisions

Senior Data Analyst specializing in customer segmentation and cost optimization through statistical analysis and machine learning. I turn raw data into clear narratives that drive strategic decisions.

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Career

Experience

3 roles across data analytics and business intelligence.

TechCorp Inc.

Junior Data Analyst

TechCorp Inc.

Full-time
San Francisco, CAJan 2022 — Present
  • Owned end-to-end analytics pipeline serving 3.2M monthly active users across 12 product lines.
  • Reduced customer churn by 8% through K-Means segmentation model deployed to production.
  • Built self-serve Tableau dashboards adopted by 40+ stakeholders across Marketing and Operations.
  • Mentored 2 junior analysts and introduced code review practices for SQL and Python notebooks.

Data Analyst

Retail Analytics Co.

Full-time
RemoteJun 2020 — Dec 2021
  • Designed and executed 15+ A/B tests on pricing and UX features, with rigorous statistical validation.
  • Automated weekly reporting pipeline using Airflow + Python, saving 6 hours of manual work per week.
  • Partnered with the supply chain team to build a demand forecasting model (MAE: 4.2%).

Data Analyst Intern

FinTech Startup

Internship
New York, NYJun 2019 — Aug 2019
  • Analyzed transaction data from 200k+ users to identify fraud patterns using SQL and Python.
  • Presented findings directly to the CTO; recommendations were implemented in Q3 2019.

Background

Education

Academic foundation and professional certifications.

2 credentials

B.Sc. Statistics & Computer Science

GPA 3.8 / 4.0

University of California, Berkeley

Berkeley, CA2016 — 2020
  • Dean's List — 6 consecutive semesters
  • Thesis: 'Predictive Modeling of Consumer Behavior in E-commerce'
  • Teaching Assistant — Intro to Data Science (2 semesters)

Data Science Professional Certificate

Coursera / Google

Online2021 — 2021
  • Completed 8-course specialization covering Python, SQL, Tableau, and ML fundamentals.
  • Capstone project scored in the top 5% of cohort.

Case Studies

The Proof

Each project is structured using the SAR framework — Situation, Action, Result — to clearly communicate impact.

Situation
Action
Result

E-commerce Customer Segmentation

PythonK-MeansSQLTableau
Situation

Customer retention rate dropped 15% YoY, with no clarity on which segments were churning or why.

Action

Cleaned and engineered features from 500k+ rows of transaction SQL data. Applied K-Means clustering to identify 5 distinct behavioral segments. Built a Tableau dashboard for the marketing team.

Result

Targeted re-engagement campaigns increased retention by 8%, saving $3,500/month in acquisition costs.

View CodeView Dashboard

Supply Chain Cost Optimization

PythonXGBoostBigQueryPower BI
Situation

Logistics costs exceeded budget by 22% across 3 consecutive quarters with no predictive visibility.

Action

Built an XGBoost regression model on 2 years of shipping data from BigQuery. Identified top 9 cost drivers and created a Power BI report for operations leadership.

Result

Model achieved 91% prediction accuracy. Recommendations led to a 14% reduction in quarterly logistics spend.

View Code

A/B Test: Homepage Conversion Uplift

PythonStatisticsSQLLooker
Situation

The product team proposed a new homepage layout but lacked a rigorous framework to measure impact on sign-up conversion.

Action

Designed and ran a two-sided A/B test for 3 weeks covering 45k users. Used Chi-square tests and bootstrap confidence intervals to validate statistical significance.

Result

Confirmed a statistically significant 2.3% uplift in conversion (p < 0.05), translating to an estimated $8,000/month in additional revenue.

View CodeView Dashboard

Technical Stack

Tools & Technologies

A curated set of tools I reach for to solve analytical problems — organized by discipline.

Data Manipulation

Core tools for wrangling and transforming data at scale.

  • Python (Pandas, NumPy)
  • SQL (PostgreSQL)
  • dbt
  • Apache Spark

Visualization

Turning numbers into charts that drive decisions.

  • Tableau
  • Power BI
  • Matplotlib / Seaborn
  • Looker

Statistical Analysis

Rigorous methods to separate signal from noise.

  • A/B Testing
  • Regression Analysis
  • Hypothesis Testing
  • Time Series

Machine Learning

Building predictive models from historical patterns.

  • Scikit-learn
  • K-Means Clustering
  • XGBoost
  • Feature Engineering

Infrastructure

Data warehouse, pipeline, and version control tooling.

  • Google BigQuery
  • AWS Redshift
  • Airflow
  • Git / GitHub