n
nidakhalil4

Nida K

@nidakhalil4

Analytical, Collaborative and Innovative

Paquistão
Inglês
Algumas informações são exibidas no idioma inglês.
Sobre mim
Hello, I'm Nida Khalil, a dedicated and experienced data analyst with a background in Statistics and a current role as a Scientific Officer. Statistician with 2+ years of professional experience in agricultural research and national survey design. Skilled in experimental design, advanced data analysis, and machine learning, with strong proficiency in R, SQL, python and Minitab. Proven track record in supporting data-driven decision-making by developing efficient sampling designs, conducting large-scale surveys, and training scientists in statistical methods.... Saiba mais

Habilidades

n
nidakhalil4
Nida K
offline • 

Conheça meus serviços

Modelagem e Análise Estatística
I will statistical modeling and data visualization using rstudio
A partir deUS$ 30 /projetoMais detalhes
Consultoria em data analytics
I will agricultural data analysis and visualization using rstudio
A partir deUS$ 50 /projetoMais detalhes

Portfólio

Experiência profissional

Scientific Officer( Statistics)

Ayub Agricultural Research Institute, Faisalabad, Punjab, Pakistan. • Período integral

Jun 2023 - Present • 2 yrs 11 mos

I am a Statistical Analyst and Data Scientist with professional experience as a Scientific Officer in the Punjab Agriculture Department. I design field, lab, greenhouse, and screen-house experiments using RCBD, CRD, Split Plot, Alpha Lattice, Factorial, and other advanced designs. I also conduct field verification across research stations to ensure proper layout, randomization, and treatment application. I analyze complex datasets using RStudio, Python, SPSS, and Excel, performing ANOVA, regression, correlation, path analysis, PCA, G×E studies, and mixed models (REML/BLUP). I interpret results for scientists and support high-quality research outputs. I also vet Annual Research Programs, review experiment methodology, maintain provincial crop statistics (area, production, yield), and train researchers in experimental design, data analysis, and software skills.