architrawat2003
About Candidate
Passionate and results-driven Data Scientist and Data Analyst with expertise in transforming complex datasets into actionable insights. Skilled in Machine Learning, Deep Learning, and Natural Language Processing, with a proven ability to develop predictive models and uncover patterns that drive strategic decisions. Proficient in Big Data technologies and cloud platforms, adept at building scalable solutions that bridge the gap between advanced analytics and business impact. Committed to delivering data-driven innovations that empower organizations to grow, adapt, and lead in a rapidly evolving digital landscape.
Location
Education
Work & Experience
1. Analyzed marketing and sales data to understand which campaigns worked best and helped improve customer targeting and lead conversions. 2. Created easy-to-read Power BI dashboards to track sales performance, regional trends, and employee productivity for better decision-making. 3. Automated reporting and data processes using Python, SQL, and Zapier, reducing manual work and enabling real-time insights. 4. Built machine learning models to predict future sales and customer trends, helping the team plan resources better. 5. Helped identify real-time investment and growth opportunities for the business using data insights.
1. Used AI tools to understand customer opinions, brand mentions, and trends from text data and connected the results with Salesforce. 2. Grouped customers into meaningful segments using data analysis to help create better marketing strategies. 3. Built systems to spot unusual changes in campaign performance early, like drops in clicks or conversions. 4. Added AI insights into dashboards like Power BI and Looker to help teams monitor campaigns, plan budgets, and improve results. 5. Worked with teams to turn data insights into useful actions for marketing campaigns.
1. Built reliable systems to process large volumes of data quickly, making it ready for analysis and machine learning. 2. Enhanced machine learning models to make more accurate predictions and reduce errors. 3. Developed automated workflows so models could update themselves when new or changing data appeared. 4. Created real-time analytics tools that helped teams make faster, smarter business decisions in fintech and power sector projects.
