Ayush Dhakad
Indore, India
Ayush Dhakad
Data Science and Analytics
Category : Artificial intelligence (AI)
I’m a Data Science and Analytics professional focused on turning raw data into clear, actionable insights. I work with Python, SQL, Excel, and visualization tools to clean data, analyze trends, and support data-driven decisions. I’m highly self-motivated, quick to learn new tools, and committed to delivering accurate, well-documented work that meets client goals and deadlines.
Working hours
- Monday:08h00 To 18h00
- Tuesday:08h00 To 18h00
- Wednesday:08h00 To 18h00
- Thursday:08h00 To 18h00
- Friday:08h00 To 18h00
- Saturday:Not available
- Sunday:Not available
1) Understand the overall sales performance, trends, and patterns over time.
2.) Analyse the distribution of product categories, sizes, and quantities sold to identify popular products.
3) Investigate the fulfilment methods used and their effectiveness in delivering orders.
4) Segment customers based on their buying behavior, location, and other relevant factors.
5) Explore the geographical distribution of sales, focusing on states and cities.
6) Provide actionable insights and recommendations based on the analysis to optimise sales
strategies, improve customer satisfaction, and enhance overall business performance.
Deliverables:
1. Comprehensive analysis report summarising key findings, insights, and recommendations.
2. Visualisations (charts, graphs) illustrating various aspects of the data analysis.
3. Insights on product preferences, customer behaviour, and geographical sales distribution.
4. Recommendations for improving sales strategies, inventory management, and customer service.
2.) Analyse the distribution of product categories, sizes, and quantities sold to identify popular products.
3) Investigate the fulfilment methods used and their effectiveness in delivering orders.
4) Segment customers based on their buying behavior, location, and other relevant factors.
5) Explore the geographical distribution of sales, focusing on states and cities.
6) Provide actionable insights and recommendations based on the analysis to optimise sales
strategies, improve customer satisfaction, and enhance overall business performance.
Deliverables:
1. Comprehensive analysis report summarising key findings, insights, and recommendations.
2. Visualisations (charts, graphs) illustrating various aspects of the data analysis.
3. Insights on product preferences, customer behaviour, and geographical sales distribution.
4. Recommendations for improving sales strategies, inventory management, and customer service.
1) Led the transition to a paperless practice by implementing an electronic booking system and a faster, safer and more accurate business system and also reduced labor cost by 30% and office overhead by 10%.
2) Supported operations by preparing and processing large datasets and enhanced business decision accuracy by 25% via detailed statistical analysis.
3) Enhanced business processes by identifying and implementing solutions and increased team productivity by 18% through collaborative process improvements.
4) Expanded technical proficiency through continuous learning and 100% data integrity by following privacy guidelines.
2) Supported operations by preparing and processing large datasets and enhanced business decision accuracy by 25% via detailed statistical analysis.
3) Enhanced business processes by identifying and implementing solutions and increased team productivity by 18% through collaborative process improvements.
4) Expanded technical proficiency through continuous learning and 100% data integrity by following privacy guidelines.
1) 40%: Using Python and SQL for data preprocessing and cleaning, ensuring data accuracy and quality for analysis.
2) 30%: Using Tableau and Power BI to build dynamic dashboards and visualisations that show insights that can be put into action.
3) 20%: Using programs like R and Excel for statistical analysis and predictive modelling in order to spot patterns and trends.
4) 10%: Working in groups to use SQL and scripting to enhance procedures and automate data workflows.
2) 30%: Using Tableau and Power BI to build dynamic dashboards and visualisations that show insights that can be put into action.
3) 20%: Using programs like R and Excel for statistical analysis and predictive modelling in order to spot patterns and trends.
4) 10%: Working in groups to use SQL and scripting to enhance procedures and automate data workflows.
Was a member of Indian Student Association (Strathclyde Indian Students Association [SISA]).
Worked on projects like Spotify top Genre prediction as well as popularity score of the song, Good Reads Recommendation System, Facial Recognition and Transformer problem using deep learning libraries and big data tools and technologies.
Worked on projects like Spotify top Genre prediction as well as popularity score of the song, Good Reads Recommendation System, Facial Recognition and Transformer problem using deep learning libraries and big data tools and technologies.
Member of university basketball club and won runner-up price in the inter-year team tournament of sports wing.
Learned Python programming through creating projects such as a phone directory and Tic Tac Toe game, while also delving into data science specifically in data processing utilizing NumPy and Pandas.
Developed a Home Automation system utilizing Arduino UNO and Google Firebase in a group project during 3rd year of study, concentrating on hardware configuration and coding assistance.
Learned Python programming through creating projects such as a phone directory and Tic Tac Toe game, while also delving into data science specifically in data processing utilizing NumPy and Pandas.
Developed a Home Automation system utilizing Arduino UNO and Google Firebase in a group project during 3rd year of study, concentrating on hardware configuration and coding assistance.
- 🇬🇧 English
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