Mahesh Yadav

• Developed ad hoc Power BI dashboard, aggregating data from diverse sources including Snowflake, Databricks, SQL, Azure DevOps, and third-party applications. Employed Microsoft BI Stack for data cleaning and transformation, leveraging Query Folding for optimization. • Skillfully managed and led analytics suites (Business Health dashboards) for various clients, optimizing performance and visual quality through consistent improvements. Leveraged Power BI's RLS for robust data security. • Optimized SQL queries and stored procedures, improving report refresh performance by 40% and implemented appropriate refresh strategies, choosing between scheduled or incremental refreshes based on specific use cases. • Delivered impactful weekly dashboards to 40+ stakeholders, whilst driving data-informed decisions and highlighting key insights. • Designed and optimized ETL pipelines for dashboards using Power Query and SQL, ensuring seamless data flow from Snowflake and other cloud sources. • Pioneered the concept of a comprehensive Power BI dashboard End to End solution, encompassing KPIs and insights, empowering 10+ business users to self-serve analytics and reduce report dependency by 30%.

• Developed ad hoc Power BI dashboard, aggregating data from diverse sources including Snowflake, Databricks, SQL, Azure DevOps, and third-party applications. Employed Microsoft BI Stack for data cleaning and transformation, leveraging Query Folding for optimization. • Skillfully managed and led analytics suites (Business Health dashboards) for various clients, optimizing performance and visual quality through consistent improvements. Leveraged Power BI's RLS for robust data security. • Optimized SQL queries and stored procedures, improving report refresh performance by 40% and implemented appropriate refresh strategies, choosing between scheduled or incremental refreshes based on specific use cases. • Delivered impactful weekly dashboards to 40+ stakeholders, whilst driving data-informed decisions and highlighting key insights. • Designed and optimized ETL pipelines for dashboards using Power Query and SQL, ensuring seamless data flow from Snowflake and other cloud sources. • Pioneered the concept of a comprehensive Power BI dashboard End to End solution, encompassing KPIs and insights, empowering 10+ business users to self-serve analytics and reduce report dependency by 30%.

In my role as a Data Analyst, I've had the opportunity to delve deep into vast datasets, uncovering and introducing new trends and patterns that have significantly enhanced data transparency. Utilizing Power BI and SQL Server Management Studio, I've transformed complex data into clear, actionable insights. One of my key initiatives has been the planning and designing of Key Performance Indicators (KPIs), specifically aimed at identifying upsell opportunities. This process has not only provided continuous access to critical metrics but has also empowered our team to make informed, strategic decisions that drive growth and success. My key contributions are: • Streamlined the migration of 240 business reports by managing a team of 4 Analysts and bridging communications between technical and non-technical units. Optimized data reliability by writing complex SQL queries and Excel/VBA integrations, while establishing a Knowledge Base of 20+ articles to ensure long-term system stability and incident resolution. • Decreased fraud by 25% and optimised downtime by 20% through the comprehensive analysis of customer data and insightful presentations to stakeholders from clients. • Maximised overall operational efficiency by 15% through optimisation of customer call routing, whilst streamlined claims processing, and automation of routine tasks. • Seamlessly integrated audit reports and customer engagement reports into the analytics system, amplifying data model performance, and compliance insights. Collaborated effectively to offer unmatched visibility and slashed audit time by 80%.

• Streamlined the migration of 240 business reports by managing a team of 4 Analysts and bridging communications between technical and non-technical units. Optimized data reliability by writing complex SQL queries and Excel/VBA integrations, while establishing a Knowledge Base of 20+ articles to ensure long-term system stability and incident resolution. • Decreased fraud by 25% and optimised downtime by 20% through the comprehensive analysis of customer data and insightful presentations to stakeholders from Aviva, Reassure, Phoenix, and Countrywide. • Maximised overall operational efficiency by 15% through optimisation of customer call routing, whilst streamlined claims processing, and automation of routine tasks.

• Increased client data acquisition, cleansing, and pre-processing using SQL and Excel, whilst ensuring data readiness and integrity. • Decreased procurement costs by 20% by creating a client dashboard providing real-time order insights and future forecasting.

During my time in this company, I became the go-to person for turning raw data into powerful stories that drove impactful decisions. Picture a room full of stakeholders grappling with countless spreadsheets that's where I stepped in. Using advanced data modeling techniques with Python and R, I transformed complex datasets into clear, actionable insights. I didn't just deliver reports; I crafted narratives that guided strategic initiatives and optimized business performance. By presenting data in a compelling way, I empowered my team to make informed, data-driven decisions, ultimately fostering a culture where every choice was backed by solid evidence and deeper understanding. My key achievements are: • Maximized client data acquisition, cleansing, and pre-processing using SQL and Excel, whilst ensuring data readiness and integrity. • Lowered procurement costs by 20% by creating a client dashboard providing real-time order insights and future forecasting.

In this role, I teamed up with senior management to embark on a transformative journey of process improvement. Our mission was clear: to uncover and tackle inefficiencies that were holding back our operational potential. Through insightful analysis and strategic collaboration, we identified key areas ripe for enhancement. Each discovery was met with a targeted initiative, designed to streamline workflows and eliminate bottlenecks. As we implemented these changes, the organization experienced a remarkable boost in efficiency and performance. This partnership not only fostered a culture of continuous improvement but also set the stage for long-term success, demonstrating the power of teamwork in driving meaningful progress. My key accomplishments are: • Increased sales by 15% by organising comprehensive data staging, integration, validation, and analysis utilising Tableau. • Improved data quality and analytical capabilities through proficient engineering of datasets with Python and SQL. • Played a key role in achieving 20% cost reduction by planning and initiating in-depth product-focused research using focus groups, whilst optimising resource allocation.

• Increased sales by 15% by organising comprehensive data staging, integration, validation, and analysis utilising excel. • Played a key role in achieving 20% cost reduction by planning and initiating in-depth product-focused research using focus groups, whilst optimising resource allocation.

My time in this company, I was dedicated to elevating key performance indicators like accessibility, mobility, and retention through a rigorous daily performance analysis. By diving deep into data and trends, I identified opportunities for improvement and implemented strategic changes that drove noticeable enhancements. My commitment extended to providing hands-on technical support to our program partners, where I tackled complex data-related challenges and worked tirelessly to strengthen system reliability. This approach not only resolved immediate issues but also contributed to long-term system stability and success.

Data Visualisation and Analytics Machine Learning models Data Cleaning, Exploration and Transformation Hypothetical Analysis

Acquired knowledge of specific techniques for applying data science to different domains, such as computer vision, social media analysis, intelligent sensing, and internet of things. Developing understanding of advanced software development, systems for big data analytics, data mining / privacy, and data visualisation / exploration. Building skillset in machine learning techniques for cluster detection, automated classification, and big data processing techniques for processing massive amounts of data.

Developed understanding of implementing and evaluating computational system to meet desired needs within realistic constraints. Acquired knowledge of utilizing appropriate techniques, skills, and tools necessary for computing practices.