Brian Wasike

WASIKE BRIAN | DATA ANALYST/ SCIENTIST (Business & Financial Analytics) PERSONAL STATEMENT Skilled in data analysis, trend identification, and data quality assessment, with hands-on experience in credit risk modeling and financial data analysis. Proficient in SQL, Excel, Python, and Power BI to transform complex datasets into actionable insights. Strong commercial acumen with the ability to translate analytics into business decisions aligned with revenue growth, cost control, and operational efficiency KPIs, supported by a solid foundation in statistics, machine learning, predictive analytics, and dashboard development. SKILLS Programming & Databases: SQL, Python, R Data Analysis & Visualization: Excel, Jupyter Notebook, power BI (DAX, data modeling, M/Power Query, Power BI Service) Microsoft Excel: Advanced (Pivot Tables, Power Query, Lookups) — Licensed desktop version installed Financial & Risk Analysis: Underwriting Data Analysis, Claims Analysis, Policy Performance Analytics, Credit Risk Assessment, Portfolio Monitoring, Business Tools: Exposure to CRM systems, ERP/accounting platforms, and online reporting tools. Soft Skills: • Problem-Solving (applied in analyzing data issues and improving workflows) • Presentation Skills (able to explain findings to technical and non-technical teams) • Time Management (able to meet reporting deadlines consistently) • Team Collaboration (worked with cross-functional teams on data projects) • Organization (manages multiple datasets and tasks with accuracy) EDUCATION Mount Kenya University- Bachelor of Science in Statistics (2022 – 2025) ALX Africa – Professional Development Skills for the Digital Age (Completed: July 2025) ALX Africa – Data Analytics (Completed: October 2025) WORK EXPERIENCE Data Scientist (Remote) – Turing Dec 2025-Feb2026 • • Develop and deploy predictive classification models (Scikit-learn) for credit risk, analogous to Claims Analysis and Fraud Detection Analytics, improving forecasting accuracy by 12%. Clean and analyze Underwriting Data and loan portfolio datasets (>100GB), enhancing data integrity for risk assessment and reducing manual processing time by 15%. Data analyst – Mombasa Maize Millers jan2025-Nov2025 • Used SQL and Python to collect, clean, and analyze key operational and financial data, supporting weekly management performance reviews. • Designed and launched 3 interactive Power BI dashboards for Sales and Operations, enabling department heads to monitor 5 key KPIs and make real-time decisions • Assessed and improved data quality by identified and resolved 150+ data inconsistencies, enhancing reporting accuracy by 95% • Collaborated with Sales, Operations, and Finance teams to translate business requirements into analytical dashboards and actionable insights. CERTIFICATIONS • Data Analysis – ALX Africa (Completed: October 2025) • Professional Development Skills for the Digital Age – ALX Africa (Completed: July 2025) PROJECTS Credit Risk Classification Built a Logistic Regression model in Python (Scikit-learn) to predict loan defaults, achieving an 88% AUC score and reducing potential financial losses. Stock Price Predictions Developed and compared ARIMA and SARIMAX time-series models (Python) to forecast asset prices, outperforming benchmark predictions by 5% accuracy. Cancer Analysis Report Analyzed a large-scale medical dataset to identify demographic and trend patterns, leveraging Power BI/Tableau to present key findings to non-technical stakeholders. REFEREES Available upon request.