Mukesh Choudhary Email & Phone Number

• Enthusiastic and insightful Data Analyst with nearly 2 years of experience, specializing in data analysis, data modeling, and delivering actionable insights to drive business success• Expert in data visualization and reporting using Power BI, Tableau, and Looker, creating interactive dashboards and comprehensive reports that empower stakeholders to make informed, data-driven decisions• Proficient in advanced Excel functionalities, including VLOOKUP, Macros, and Pivot Tables, to efficiently manage, analyze, and automate complex datasets, enhancing operational efficiency• Strong database management skills with hands-on experience in MS SQL Server, SSIS/SSRS, and Snowflake, ensuring robust data architecture, seamless integration, and optimized data retrieval processes• Adept in programming and scripting with languages like Python, R, VBA, and SAS, utilizing these tools to automate workflows, develop predictive models, and perform advanced statistical analyses• Experienced in data analysis and modeling, applying Power Query, DAX, and machine learning algorithms to transform raw data into actionable insights that support strategic business objectives• Skilled in data transformation and ETL processes, leveraging ETL tools and Azure to ensure efficient data extraction, transformation, and loading, while maintaining high data accuracy and integrity• Extensive knowledge in enterprise resource planning (ERP) systems, particularly SAP, optimizing business processes and data management to improve overall operational efficiency and reporting• Proficient in data cleaning and preparation, using tools like Open Refine and Talend to ensure data quality and consistency, enabling accurate and reliable analysis• Strong understanding of statistical analysis with practical experience in using R, Excel, and SPSS for uncovering trends, correlations, and actionable business insights• Expertise in database and data storage solutions, including MongoDB and Cassandra, ensuring scalable and efficient data management that supports large and complex datasets• Adept in data querying and visualization, utilizing SQL Server, Management Studio, and MySQL Workbench to extract, analyze, and visualize data, providing clear and concise insights to stakeholders• Versatile in utilizing IDES and text editors such as Jupyter Notebook, Visual Studio Code, and RStudio, streamlining the coding process for data analysis and enhancing collaboration

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  Data Analyst

  Rbc

  Jan 2023 - Present - Toronto, Ontario, Canada

  • Integrated diverse data sources from multiple departments across Canada, streamlining data consolidation processes to ensure accuracy and consistency for robust financial and insurance reporting.• Spearheaded data cleaning and preparation using advanced SQL and Python techniques, significantly enhancing data quality and reliability for predictive analytics and risk assessment.• Optimized datasets by refining and tuning key data attributes, resulting in improved reliability for analysis and supporting more accurate risk assessment and policy pricing strategies.• Conducted in-depth exploratory data analysis (EDA), uncovering valuable insights into customer behavior and product performance, directly informing strategic decision-making.• Collaborated with senior stakeholders to identify data-driven opportunities, leading to actionable insights that enhanced performance and guided strategic initiatives within the insurance sector.• Refined and improved statistical models (Linear Regression, Logistic Regression, Random Forest) in Python, increasing the accuracy of pricing predictions, which drove more competitive and profitable product strategies.• Developed predictive models utilizing advanced statistical methods in R and Python to inform underwriting decisions and financial forecasting, improving decision accuracy.• Created dynamic, interactive dashboards using Power BI to enable real-time monitoring of key financial and insurance metrics, facilitating data-driven decision-making by stakeholders.• Automated data collection processes using Azure Databricks and SQL, achieving a 100% reduction in data collection time, driving productivity and operational efficiency for the team.• Provided critical data insights and actionable recommendations, resulting in a 20% improvement in KPI performance, directly impacting business outcomes.