Position: Data Analyst
Category: Data Analyst
English level: fluent
Years of experience: 7


Implemented devices quality tracking dashboards in power BI based on data coming from different sources (SAP, MS SQL server, snowflake, excel files) and various formats.
Tracked and analyzed data quality, anomalies during data collection process using various ML models and python. Developed rules (mainly SQL queries) for data quality governance and monitoring.

Improved customers segmentation implementing KMeans clustering. The new segmentation improved main KBIs visit and order strike rates (estimated +2pp and +5pp respectively) by
decreasing the quantity of not productive visits and calls. Respective tracking dashboards created in power bi for main business KPIs.

Led web customer portal implementation for Armenian market.
Conducted and analyzed customer satisfaction survey to measure current
satisfaction with respective dashboards. As a main outcome, market investments in specific festive periods were increased and estimated 14% revenue increase was captured
in these periods.

Collaborated with centralized data science team on orders and execution
activities suggestion model development and implementation for market
developers. The estimated outcome for the project was $50K revenue
increase in 1 year.

Participated in image recognition implementation project for market execution tracking, aimed to shorten time spent for execution evaluation and external audit cost optimization.

Projected weekly, monthly, quarterly and yearly sales volumes per product/
region, based on time series data and predictive modeling, current trends and other significant
factors. Improved weekly and monthly forecast accuracy results from 72% to 76%
and 81% to 83% respectively through implementing SARIMA models in forecasting process.

Collaborated with marketing, financial, supply chain departments on
business plan creation for upcoming 1-3 years.

Implemented automated reporting and dashboards in power BI and SQL, reducing manual work and time spent on updates.
Seeking complex data challenges to discover insights and drive valuable change