Swapnil Pokale

Operations Associate

Bengaluru, Karnataka, India2 yrs 9 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Developed a predictive model improving operational efficiency.
Hands-on experience in fintech and ad-tech industries.
Strong analytical skills with a focus on data-driven solutions.

Stackforce AI infers this person is a Machine Learning enthusiast with a focus on Fintech and Data Analysis.

Contact

pswapnil1809@gmail.com LinkedIn

Skills

Core Skills

Machine LearningData Analysis

Other Skills

Analytical SkillsAnalyticsAndroid StudioBPMN WorkflowBack-End Web DevelopmentBusiness AnalysisBusiness StrategyCommodity MarketsData StructuresEngineeringFinanceFlaskGitHTML/CSSIntelliJ IDEA

About

Self-motivated individual with the utmost curiosity to learn about technological implications on 21st-century businesses. Passionate problem solver and product enthusiast with an avid interest in the fintech and ad-tech industry, hands-on experience in programming, product analytics, risk management, and stakeholder management. As a team player, looking up opportunities to contribute, learn, level up, and grow.

Experience

Goldman sachs

2 roles

Associate

Promoted

Nov 2025 – Present · 4 mos · Bengaluru · On-site

Analyst

Jul 2023 – Nov 2025 · 2 yrs 4 mos · Bengaluru · On-site

Inmobi

Intern

Jan 2023 – Jun 2023 · 5 mos · Bengaluru, Karnataka, India

Goldman sachs

Summer Analyst

Jun 2022 – Jul 2022 · 1 mo · Bengaluru, Karnataka, India

Jsw steel

Machine Learning Intern

May 2021 – Jul 2021 · 2 mos

Developed a Machine Learning model to predict properties of Electrical Steel such as B50, Core Loss After Aging, Core Loss before Aging, Permeability, and Hardness, thus improving the firm’s operational efficiency.
Attained high prediction accuracies using Random Forest Algorithm: Hardness - 98.12%, Core Loss before Aging - 94.10%, Core Loss after Aging - 93.17%, B50 - 83.6%, Permeability - 86.12%.
Employed tech stack: HTML/CSS for Fronted, Flask for Back end, and Machine Learning libraries such as NumPy,
sci-kit-learn, and pandas for model development.

Machine LearningRandom Forest AlgorithmHTML/CSSFlaskNumPysci-kit-learn+2