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As a highly experienced data professional, I specialize in defining and implementing metrics, KPIs, and performance insights to drive business success. My background in business analysis and data analysis/business intelligence allows me to effectively understand and meet business requirements, creating operational dashboards and performance insights. My expertise in data science enables me to perform advanced analytics on large data sets and automate data extraction and transformation processes.

In my previous experience in the banking industry, I successfully managed data for 10 banks with over 10 million customers and 1 trillion transactions, including international transactions, deposits, card services, and loan services. In the e-commerce industry, I worked on a platform with over 5 million monthly active users, where I was responsible for developing and executing successful marketing campaigns, ad-services, and e-CRM strategies.

In addition to my analytical skills, I possess a range of soft skills that are essential for effective collaboration and communication with stakeholders. These include the ability to meet deadlines, prioritize tasks, and manage time effectively, as well as the ability to negotiate, persuade, and think critically.

I am proficient in a range of technical skills, including data collection and review, data and statistical analysis, business and technical analysis, and data modeling. I have experience with programming languages such as R, Python, and SQL, as well as tools such as Rapid Miner, Power BI, Tableau, and QlikView.

Mohammed Torbati's Projects

customer-data-profile icon customer-data-profile

An ETL (Extract, Transform, Load) project was implemented to build comprehensive customer data profiles from various source systems into a data warehouse.

customer-lifetime-prediction-using-python icon customer-lifetime-prediction-using-python

What is CLV or LTV? CLV or LTV is a metric that helps you measure the customer's lifetime value to a business. In this kernel, I am sharing the customer lifetime value prediction using BG-NBD, Pareto, NBD & Gamma Model on top of RFM in Python.

retentioneering-tools icon retentioneering-tools

Retentioneering: product analytics, data-driven customer journey map optimization, marketing analytics, web analytics, transaction analytics, graph visualization, and behavioral segmentation with customer segments in Python. Opensource analytics, predictive analytics over clickstream, sentiment analysis, AB tests, machine learning, and Monte Carlo Markov Chain simulations, extending Pandas, Networkx and sklearn.

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