Hello! I'm Aayush Yagol, a passionate data analyst with experience in transforming complex data into actionable insights. My journey in data analytics began during my undergraduate studies in Statistics, where I discovered my passion for finding patterns and stories hidden within numbers.
I believe that data is the most powerful tool we have for making informed decisions in today's world. My approach combines rigorous statistical analysis with creative visualisation techniques to make data accessible and meaningful to stakeholders at all levels.
Beyond my professional work, I'm an avid photographer, amateur filmmaker, and electronic music producer. These creative pursuits complement my analytical mindset and help me approach data problems from unique perspectives.
I'm constantly learning and expanding my skillset, currently exploring advanced machine learning techniques and their applications in business intelligence. I'm always open to new challenges and opportunities to collaborate on interesting data projects.
Work Experience
- Analysed claim trends using SQL and Excel, identifying key factors contributing to delays and inefficiencies.
- Developed dashboards in Google Data Studio to track claim resolution times, improving efficiency by 15%.
- Collaborated with cross-functional teams, integrating data-driven insights into strategic decision-making.
- Applied a biopsychosocial approach, leveraging data insights to enhance return-to-work success rates.
- Utilised customer data to optimise sales strategies, leading to a 10% increase in upselling success.
- Developed an Excel-based sales tracker, improving inventory forecasting accuracy.
- Engaged in data-driven decision-making, using historical sales data to anticipate customer preferences.
- Analysed customer feedback trends using Excel and Python, identifying key service improvement areas.
- Automated customer response tracking, reducing manual processing time by 20%
- Led data-driven marketing strategies, using Google Analytics to optimise branding campaigns.
- Analysed customer engagement data, improving conversion rates through targeted digital content.
- Managed datasets for product testing, providing insights that refined design decisions.
Education
Specialised in predictive modeling and machine learning algorithms. Thesis: "Optimising Customer Segmentation Models for E-commerce Platforms"
Minor in Computer Science. Graduated with honors (3.8 GPA). Research Assistant in the Department of Statistical Analysis.
Certifications
Technical Skills
- SQL
- Python (Pandas, NumPy)
- Excel, Google Sheets
- Tableau
- Power BI
- Matplotlib, Seaborn
- D3.js
- Scikit-learn
- Statistical Modeling
- Time Series Analysis
- Natural Language Processing
- KPI Development
- Dashboard Design
- ETL Processes
- Data Storytelling
Soft Skills
Analytical approach to identifying and resolving complex data challenges
Ability to explain complex data concepts to non-technical stakeholders
Experience leading data teams and coordinating cross-functional projects
Evaluating information objectively to form well-reasoned conclusions
Quick to learn new tools and technologies as data landscapes evolve
Meticulous approach to data quality and accuracy in analysis
Organising and executing data projects from conception to completion
Innovative approaches to data visualisation and problem-solving