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Marjan Sohrabi

@marjansohrabi

Data analyst with PhD candidacy in Statistics delivering scalable data pipelines and Bayesian insights.

Iran
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What I'm looking for

I seek analytic roles where I can build scalable data pipelines, apply Bayesian and statistical methods, influence policy/business decisions, and grow toward research or technical leadership.

I am a detail-oriented data analyst and PhD candidate in Statistics with over five years of experience applying statistical modeling, Bayesian inference, and scalable data architecture across health, education, and economic sectors. I have designed scoring and ranking algorithms, forecast models for insurance premiums, and led teams to ingest multi-decade national datasets to improve accessibility and query performance.

I combine strong technical skills in R, Python, SQL and Power BI with hands-on experience in quantitative risk assessment and survey-based analysis to inform policy and business decisions. I am committed to building reliable data pipelines, producing actionable visualizations, and mentoring others while maintaining rigorous statistical standards.

Experience

Work history, roles, and key accomplishments

FC

Data Analyst

Financial Data Processing Company

Jan 2021 - Dec 2024 (3 years 11 months)

Designed a scoring algorithm for a language-learning application and forecasted insurance companies' premiums while supervising an 11-person team to enter 40 years of national statistics, improving data accessibility and query performance.

Education

Degrees, certifications, and relevant coursework

FM

Ferdowsi University of Mashhad

Doctor of Philosophy, Statistics

PhD candidate in Statistics conducting research in survival analysis and Bayesian inference with related publications and conference submissions.

FM

Ferdowsi University of Mashhad

Master of Statistics, Statistics

Grade: 3.91 / 4.0

Master of Statistics focusing on survival analysis and proportional hazards models with high academic distinction.

FM

Ferdowsi University of Mashhad

Bachelor of Applied Statistics, Applied Statistics

Grade: 3.1 / 4.0

Bachelor of Applied Statistics with coursework in time series, linear models, and statistical modeling.

Tech stack

Software and tools used professionally

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