Bioinformatics / Omics Data Expert

Novartis • Cambridge, MA

5d • $103,600 - $192,400 • Hybrid

About The Position

The Oncology Data Science (OncDS) team in Biomedical Research provides computational biology, AI, and data expertise, working on projects across the pre-clinical to clinical development pipeline with novel therapeutics. OncDS specializes in using high-throughput genomic and biomarker data for target identification, drug discovery, and clinical development. This role is for a Scientific Data Engineer at the beginning of their professional data journey, supporting the development, maintenance, and modernization of FAIR oncology reference datasets. The position involves hands-on data curation, workflow automation, AI-enabled process improvement, dataset refresh and quality control, and data engineering to ensure oncology data assets are reliable, reproducible, and ready for scientific use. The role will collaborate with senior team members and cross-functional teams to modernize data curation processes, identify AI automation opportunities, and contribute to high-value reference datasets supporting Oncology-wide data strategy and FAIR data goals. It is designed to build practical experience in scalable data practices, operational excellence, and automation-driven continuous improvement. This is an opportunity to work at the intersection of data engineering, computational biology, and oncology research, contributing to data assets that enable important scientific decisions across the drug discovery pipeline. The candidate will join a collaborative team that values curiosity, learning, and continuous improvement, with opportunities to grow technical and scientific skills while building reliable, scalable data foundations for cutting-edge oncology research.

Requirements

• Degree in bioinformatics, computational biology, data science, computer science, or a related field, or equivalent relevant experience
• Experience working with omics datasets in a research environment
• Proficiency in one or more programming languages used in data science or bioinformatics, such as Python or R
• Experience with data wrangling, data quality control, and reproducible analysis workflows
• Familiarity with workflow automation and scripting for recurring data processing tasks
• Familiarity with database principles and sound data modeling practices, including normalization, primary keys, joins, and thoughtful handling of missing values and data integrity issues
• Knowledge of version control and Unix / Linux-based working environments
• Strong organizational skills and attention to detail, with a demonstrated interest in operational excellence
• Ability to learn quickly, manage multiple tasks, and work effectively in a collaborative environment
• Excellent written and verbal communication skills, and the ability to work effectively across technical and scientific teams

Nice To Haves

• Experience with oncology datasets, translational research data, or biomedical reference data resources
• Familiarity with FAIR data principles, metadata curation, or scientific data stewardship
• Experience maintaining reference datasets or supporting data products used by multiple stakeholders
• Experience collaborating with experimental scientists or lab-based partners

Responsibilities

• Work with senior team members to identify opportunities for simplification, automation, and continuous improvement in operational data processes, including modernization of data curation workflows
• Support the development and improvement of automated workflows for data processing, quality control, recurring dataset updates, and AI-enabled process improvement
• Collaborate with cross-functional teams to curate, maintain, and improve key oncology reference datasets, with an emphasis on quality, correctness, reproducibility, and operational reliability
• Contribute to reference dataset lifecycle management, including documentation, versioning, and traceable update processes
• Assess dataset structure, integrity, and fitness for downstream scientific use, including attention to identifiers, primary keys, missing values, consistency, and related data quality issues, and help resolve data issues in collaboration with relevant partners
• Contribute to best practices for reproducible workflows, data handling, and scalable dataset operations
• Help keep oncology reference datasets current, usable, and responsive to evolving scientific and organizational priorities

Benefits

• Comprehensive benefits package including health, life and disability benefits
• 401(k) with company contribution and match
• Performance-based cash incentive
• Eligibility for annual equity awards (depending on role level)
• Generous time off package including vacation, personal days, holidays and other leaves

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Associate degree