Balal G. Email & Phone Number

København, Hovedstaden, Danmark

• Built and developed an automated data quality reporting in an interactive dashboard, that helps the data team gain insight of data quality of important finalized tables. Such as completeness of data fields, company types, etc. • Automated reporting of amazon servers' performance activity, using dashboard grafana. Resulting backend team alerted proactively to prevent crashes of servers. Added dashboard alerting team on failed ETL pipelines, improved overall uptime.• Automation of labor-intensive tasks in Hubspot, using API integrations, resulting in improved workflows and smoother customer support. Implemented reverse ETL process to improve and update data fields for companies/contacts in Hubspot. • Automated reporting of usage from customers using platform and API integrations. This helps the customer success team to successfully onboard and reducing churn. • Built and developed a model based on usage data predicting churn, this helped the customer success team to mitigate churn rates. • Automated delivery of quarterly reports to stakeholders, reporting of SaaS metrics. Such as indicating revenue retention and churn rates.• Built and maintained data warehouse using, python and SQL, and implemented ETL job processes running according to schedules in Airflow

Københavnsområdet, Danmark

• Developed and maintained dashboard in Kibana, showcasing game analytics models• Made ETL data processing pipeline, using Kafka data-integration tool, in elastic database, and applied functions in LUA to clean the raw data for analytical models in Kibana Dashboard• Analyzing user behavior and interests level in the games using probability statistical models

Københavnsområdet, Danmark

• Created model, using DAX in PowerBI predicting prices of suppliers products to their consumers, based on statistical tests• Applied ARIMA time-series model in R, to predict price changes of specific retail food products based on seasons• Helped maintain dashboard

Københavnsområdet, Danmark

• Applied timeseries model to predict operational failure of ship equipment• Developed dashboard, with overview of the occurrences of different type of errors and their trends over time. That helped our potential customers in setting best suited operational parameters of their systems, to prevent further complications and optimised running