Open to opportunities

Tanushree Naik

@tanushreenaik

Message

Bioinformatics Engineer turning genomic data into scalable pipelines and faster insights.

United States

Message

What I'm looking for

I’m seeking a remote-ready role where I can build reproducible HPC genomic pipelines, automate workflows in Python, and collaborate cross-functionally to deliver measurable speed and accuracy gains for data-driven decisions.

I’m a Bioinformatics Engineer with a Ph.D. in Biology and 10+ years developing algorithms and executing data-driven solutions in high-performance Linux environments. I build reproducible, scalable genomic pipelines and user-centric analysis tools that have optimized client data processing times by up to 90%.

I automate end-to-end workflows with Python, integrate databases and APIs, and apply high-performance parallel computing to large-scale genotypic, pedigree, and sequencing datasets. I’ve co-developed tools like PedTools, and I’ve used Bayesian modeling and mixed linear approaches to help breeders integrate genetic data—reducing selection timeframes from 7 years to 2 years.

I’m highly autonomous and remote-ready, with experience collaborating asynchronously across industry-academic teams. I also create technical documentation and curriculum focused on High-Performance Computing (HPC) to help stakeholders translate complex pipeline performance into action.

Experience

Work history, roles, and key accomplishments

Data Scientist and Researcher

Independent Consultant

Jan 2020 - Jan 2025 (5 years)

Built and maintained scalable, reproducible bioinformatics pipelines in Python and shell scripting, including co-developing PedTools to reduce client data-processing time by 90%. Developed Bayesian/mixed-model analysis pipelines to shorten genetic selection timelines from 7 years to 2 years and integrated crop ontology models and external APIs into unified query-ready systems.

Python Shell Scripting Parallel Computing Git Github Database Integration API Integration Docker High Performance Computing (HPC)

Agro-Informatics Researcher

University of Minnesota

Jan 2019 - Jan 2020 (1 year)

Engineered parallel computation pipelines on Linux supercomputers to ingest and clean large genotyping datasets, reducing processing time from several days to under an hour. Partnered with agro-discovery clients (e.g., PepsiCo) to resolve data inconsistencies and implemented a Flask-based data cleaning application integrated into the GEMS platform for multi-user collaboration.

Linux High Performance Computing (HPC)Parallel Computing Data Wrangling Genotyping Data Engineering Performance Optimization Flask

Postdoctoral Fellow

University of Minnesota

Jan 2017 - Jan 2018 (1 year)

Ran Python-based NGS analysis pipelines using mothur on Linux for microbiome sequencing and applied ANOVA and PCA to support biological insights. Authored R automation for high-throughput dataset handling, reducing manipulation time by 75%, contributing to 2 peer-reviewed manuscripts and 1 research grant proposal, and helped establish a BSL2 facility within 2 months of hire.

Mothur Python ANOVA Statistical Data Analysis Scientific Writing

Graduate Researcher

Indian Institute of Science

Jan 2010 - Jan 2016 (6 years)

Conducted hypothesis-driven deep genomics research to discover a novel biosynthetic pathway in endophytic fungi and model enzyme kinetics using linear and non-linear regression in R. Presented complex results across multiple departmental symposia and national and international conferences.

Enzyme Kinetics Regression Modeling R Statistical Analysis Data Visualization