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Data with 1+ years in Machine Learning & Data Analysis
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Data Science professional skilled in Machine Learning, Data Visualization, and Marketing Analytics with 1.7 years of experience. Proven ability to apply advanced algorithms for predictive modeling, improve model accuracy, and generate actionable insights for data-driven decision-making. Adept at building interactive dashboards, optimizing marketing spend, and enhancing reporting efficiency, with a strong foundation in Mechanical Engineering and a focus on data-centric electives.
University of Europe for Applied Sciences
Master of Science · Data Science
August 1, 2023 – June 30, 2024
Vishwakarma Institute of Information Technology
Bachelor of Technology · Mechanical Engineering
August 1, 2018 – June 30, 2022
Scientific Reports (Nature Portfolio)
Co-Author (Machine Learning and Data Analysis)
October 1, 2025 – December 31, 2025
Berlin, Berlin, Germany
University of Europe for Applied Sciences (UE)
Research Intern – Hand Gesture Recognition Using AlΙ
September 1, 2024 – November 1, 2024
Potsdam, Brandenburg, Germany
Kadamba Foods (e.V)
Data Analytics and Marketing intern
April 1, 2024 – September 1, 2024
Berlin, Berlin, Germany
Autofac Technologies
Data Analyst
January 1, 2022 – February 1, 2023
Chennai, Tamil Nadu, India
Excel Sales Dashboard generation
June 1, 2024 – June 1, 2024
Designed an Excel-based interactive dashboard, reflecting firm-wide revenue, profit margins, and return on investment (ROI). Implemented pivot tables, graphs, and geospatial mapping to visualize business performance and highlight operational efficiency gaps. Developed data-driven process insights, assisting leadership in optimizing financial strategies and resource allocation
Sales Dashboard generation
June 1, 2024 – June 1, 2024
Developed an interactive Power BI dashboard for a pizza delivery company, integrating sum of profit, revenue, map locations, and operational metrics to provide actionable business insights. Applied data modeling, KPI tracking, and dashboard automation to optimize sales performance reporting. Designed compelling visualizations and dynamic reports, enhancing data-driven decision-making for stakeholders.
Crypto Price Analysis and World Financial Order
June 1, 2023 – September 1, 2023
Conducted XRP trend analysis as part of a Data Science and Business module, evaluating market trends and investment risks. Utilized Python for data analysis and predictive analytics, applying statistical modeling and time series forecasting to assess crypto price fluctuations. Created interactive financial dashboards to visualize the impact of macroeconomic factors on cryptocurrency performance.
Excel certifications
Great Learning Applied
October 1, 2022 – Present
Python: Building Projects with Python Programming
Udemy
September 1, 2022 – Present
Supply Chain Logistics
Coursera
September 1, 2020 – Present
Renewable Energy and Green Building Entrepreneurship
Coursera
September 1, 2020 – Present
Successful Presentation
Coursera
September 1, 2020 – Present
Teamwork Skills: Communicating Effectively in Groups
Coursera
September 1, 2020 – Present
Matlab Programming for Numerical Computation
NPTEL
March 1, 2019 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from sales dashboards to crypto price analysis and public health policy, indicates a broad interest in applying data science across various domains. The experience as a co-author and research intern suggests a collaborative and research-oriented mindset. The academic background in Data Science aligns well with a target Data role, showing a commitment to the field. The internships at Kadamba Foods and Autofac Technologies demonstrate adaptability to different organizational contexts.
Soft Skills & Operational Fit
The candidate demonstrates analytical thinking, attention to detail, communication, stakeholder collaboration, and problem-solving skills. These soft skills are crucial for a data role, enabling effective interpretation of data, clear presentation of findings, and collaborative problem-solving within a team. The project descriptions indicate an ability to translate technical insights into actionable business recommendations, which is a strong operational fit.