A detail-oriented Data Analyst, has a postgraduate degree in Mathematics, as well as real-world experience in the entire data lifecycle, including data extraction and cleaning, advanced analysis, modeling, and visualizat…
A detail-oriented Data Analyst, has a postgraduate degree in Mathematics, as well as real-world experience in the entire data lifecycle, including data extraction and cleaning, advanced analysis, modeling, and visualization. Experienced in Python, SQL, Power BI, and statistical analysis, has a solid capability to turn complex data into understandable and practical information to business stakeholders. Love to use data to make smarter decisions, make operations more efficient and solve real-world problems.
Saved 40% of data preparation time by creating automated Python (Pandas) scripts to clean and standardize 5,000+ rows of raw data, eradicating repeat and reoccurring hand-processing errors.
Conducted a thorough statistical analysis on survey data using SPSS, which revealed changes in consumer preference that were used to shape the planning of leadership strategies.
Transformed weekly reports into visual dashboards with Advanced Excel and cut the time on data exposition across meetings by 20%.
Collaborated with cross-functional groups in the creation of data dictionaries and documentation, enhancing data interpretation consistency and reliability across departments.
Saved 40% of data preparation time by creating automated Python (Pandas) scripts to clean and standardize 5,000+ rows of raw data, eradicating repeat and reoccurring hand-processing errors., Conducted a thorough statistical analysis on survey data using SPSS, which revealed changes in consumer preference that were used to shape the planning of leadership strategies., Transformed weekly reports which had a lot of text in them into visual dashboards with Advanced Excel and it cut the time on data exposition across meetings by 20%., Collaborate with cross-functional groups in the creation of data dictionaries and documentation, enhancing data interpretation consistency and reliability across departments.
Increased data accessibility of complex SQL queries by 30 percent by writing and optimizing, so that structured datasets are available on time to modeling teams.
Translated static operational reports into interactive Power BI dashboards, which would allow monitoring the KPIs in real-time and quicker decision-making.
Created a customer churn prediction model with Scikit-learn, with 82% accuracy, and proved that proactive customer retention plans are possible.
Did extensive Exploratory Data Analysis (EDA) of the data with Matplotlib and Seaborn to identify outliers and distribution patterns to provide quality analytical inputs.
Increased data accessibility of complex SQL queries by 30 percent by writing and optimizing, so that structured datasets are available on time to modeling teams., Translated the non-interactive static operational reports into interactive Power BI dashboards, which would allow monitoring the KPIs in real-time and quicker decision-making., Created a customer churn prediction model with Scikit-learn, with 82% accuracy, and proved that proactive customer retention plans are possible., Did extensive Exploratory Data Analysis (EDA) of the data with Matplotlib and Seaborn to identify outliers and distribution patterns to provide quality analytical inputs.
نظام التوظيف التشغيلي المعتمد على الذكاء الاصطناعي أولاً، الذي يوحّد ويؤتمت دورة التوظيف بالكامل للمؤسسات الحديثة حول العالم.
د.جوب منطقة حرة ذ.م.م. 2026 © جميع الحقوق محفوظة
