Genetics and Plant Breeding | Genomics | Bioinformatics | Data Analysis and Visualization |
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
ICAR- Indian Agricultural Statistics Research Institute (IASRI)
Data Scientist
June 16, 2026 – Present
Primer-design-pipeline
January 9, 2026 – Present
Lightweight primer design pipeline for SNPs and indels with isPCR-based off-target validation. No database required.
View ProjectKasp_Extractor
January 7, 2026 – Present
Python tool to extract flanking sequences from VCF files for KASP primer design. Batch processing support with zero dependencies.
View ProjectRNA_seq-Hisat_stringTie
January 7, 2026 – Present
RNA_seq-Hisat_stringTie — GitHub repository
View ProjectVariant_calling_GATK
January 7, 2026 – Present
GATK-based variant calling pipeline for genomic analysis
View ProjectGWAS-using-GAPIT-in-R
April 9, 2024 – Present
Comprehensive GWAS analysis toolkit using GAPIT R package. Includes scripts, documentation, and example workflows for identifying genetic variants associated with traits using GLM, MLM, BLINK, and FarmCPU models
View ProjectCultural Fit Analysis
The candidate's projects are heavily concentrated in bioinformatics and agricultural genomics. While this demonstrates deep domain expertise, the lack of diversity in project types or industries might indicate a narrow focus. The current role as 'Data Scientist' at an agricultural institute aligns with their project portfolio, suggesting a fit for roles requiring specialized biological data analysis. However, for a broader 'Data Scientist' role, a lack of experience in general machine learning, business intelligence, or diverse data science applications might be a concern.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a focus on technical execution and problem-solving within bioinformatics. Information on collaboration, project management, or communication in a team setting is not provided, making it difficult to assess soft skills and operational fit.