Job Description

Position Title : Data Scientist - Bioinformatician Department : Bioinformatics / Research / Life Science Location : Hyderabad Type : Full-time Job Overview : We are seeking a highly skilled Bioinformatician with expertise in transcriptomics and next-generation sequencing (NGS) analysis, including mRNA-seq, Ribo-seq, and tRNA-seq pipelines. The ideal candidate will be responsible for developing and executing data analysis pipelines for high-throughput sequencing projects, with a focus on transcriptomics and multi-omics data integration. This position offers an excellent opportunity to contribute to cutting-edge research in a collaborative and dynamic environment. Key Responsibilities : Design, implement, and optimize bioinformatics pipelines for RNA sequencing (RNA-seq), ribosome profiling (Ribo-seq), and tRNA sequencing (tRNA-seq) analysis. Perform comprehensive analysis of mRNA expression data, differential gene expression, and alternative splicing events. Preprocess and analyze transcriptomics datasets, including GEO data preprocessing, data normalization, and integration. Utilize advanced statistical techniques and bioinformatics tools for data analysis and interpretation. Work with multi-omics data, integrating transcriptomics with genomics, proteomics, and other relevant datasets. Conduct quality control of raw sequencing data and produce comprehensive reports for research teams. Develop custom scripts and workflows in R and Python to enhance analysis and visualization capabilities. Collaborate with cross-functional teams, including wet lab scientists and computational biologists, to support ongoing research projects. Stay updated with the latest developments in transcriptomics and bioinformatics tools and methodologies. Qualifications : Education : PhD in Bioinformatics, Computational Biology, transcriptomics, or a related field, OR a Masters degree with relevant experience (2-3 years) in a related area. Experience : Minimum of 2-3 years of hands-on experience in bioinformatics, with a focus on transcriptomics analysis. Proven experience working with RNA-seq, Ribo-seq, and tRNA-seq data analysis pipelines. Strong background in transcriptomics, including gene expression analysis, differential expression, and data normalization techniques. Experience with multi-omics data integration and analysis. Technical Skills : Proficiency in R and Python for data analysis, statistical modeling, and visualization. Hands-on experience with bioinformatics tools and software such as STAR, TopHat, DESeq2, edgeR, Cufflinks, and others relevant to RNA-seq and related technologies. Familiarity with multi-omics databases and resources such as GEO, Ensembl, and others. Strong knowledge of data preprocessing and quality control steps, including handling large datasets and big data. Familiarity with version control systems (e.g., Git) and experience working in a Linux/Unix environment. Knowledge AI/ML Deep learning models.