Shivanshu Giri

Head of Design

Dehradun, Uttarakhand, India3 yrs 2 mos experience

Most Likely To Switch

Key Highlights

Proficient in Data Science and Statistical Analysis.
Experienced in developing Python-based analytical solutions.
Strong background in Financial Markets and Quantitative Research.

Stackforce AI infers this person is a Data Science and Financial Analysis professional with strong analytical capabilities.

Contact

Skills

Core Skills

Data ScienceStatistical Data AnalysisQuantitative ResearchFinancial Markets

Other Skills

Alpha GenerationAlpha TestingArcGIS ProBehavioral FinanceBiasBusiness PlanningBusiness StrategyCommunicationData AnalysisData AnalyticsData VisualizationEconomic DevelopmentFinanceInterpersonal SkillsLarge-scale Data Analysis

Experience

Quizzing section, iit roorkee

2 roles

Additional Secretary

May 2025 – Aug 2025 · 3 mos

Member

Feb 2024 – Present · 2 yrs 1 mo

Photography section, iit roorkee

2 roles

Secretary

May 2025 – Present · 10 mos · Roorkee, Uttarakhand, India

Joint Secretary

May 2024 – Apr 2025 · 11 mos · Roorkee, Uttarakhand, India

Zintlr

AI-ML Intern

May 2025 – Jul 2025 · 2 mos · Remote

Directorate of economics and statistics (des)

Summer Intern

Jul 2024 – Sep 2024 · 2 mos · Hybrid

Analyzed research papers and United Nations Development Program reports facilitating development and calculation of Multidimensional Poverty Index of a country using individual or household datasets of various deprivations.
Developed a Python code for calculating Multidimensional Poverty Index using National Survey Scheme dataset for Uttarakhand state, District-wise as well as segregated by rural and urban areas.
Articulated and identified major areas of deprivations among the public for each district of Uttarakhand based on Urban and Rural households.

Large-scale Data AnalysisData SciencePython (Programming Language)Pandas (Software)Report WritingResearch Skills+2

Indian institute of technology, ropar

Summer Research Intern

May 2024 – Jun 2024 · 1 mo · Ropar · On-site

Analyzed over 20 Research papers to study Crop Yield Prediction Model based on Non-Linear Regression approach (Quasi-Newton Method).
Collected and preprocessed dataset with over 2000 data points of Normalized Difference Vegetation Index (NDVI), Soil Moisture, Average daily precipitation and Land Surface Temperature for the state of Illinois, USA.
Analyzed a pretrained model based on piecewise Non-Linear Regression approach for corn and soyabean crops on Iowa, USA dataset and implemented it successfully on Illinois, USA for the crops corn and soyabean with 82% accuracy.

Data AnalysisData VisualizationResearch Skills