Remote Sr Data Scientist/Data Engineer

Description:

• Nomic is focused on making biology easier to measure through its nELISA platform, which is the highest throughput proteomic platform available.
• The company has partnered with top-tier drug discovery groups and has profiled over 60 million proteins from more than 400,000 samples.
• The Data team is responsible for designing, building, operating, and improving data pipelines, infrastructure, and tools for analyzing nELISA data at scale.
• The role involves building robust data pipelines, developing internal tools for scientists, and improving data processing algorithms.
• Daily responsibilities include designing and automating data pipelines for processing flow cytometry data, interpreting nELISA experimental data, and developing new data analysis pipelines.
• The position requires substantial communication and teamwork, especially in troubleshooting nELISA data issues.

Requirements:

• A graduate degree or equivalent experience in bioengineering or a related quantitative field, focusing on biosensors or quantitative fluorescence data is required.
• At least 3 years of experience in analyzing bioscience data and developing data processing algorithms is necessary.
• A minimum of 2 years of software engineering experience is required, with comfort in creating tools for non-programmers and collaborating with data and software engineers.
• Strong statistical skills, including knowledge of Bayesian statistics and sampling methods, are essential.
• Experience working collaboratively with wet lab scientists in a fast-paced environment is preferred.
• Nice to have: Understanding of life science tools and technologies, particularly in immunoassays and DNA biosensor designs.
• Excellent communication skills and independent problem-solving abilities are required.
• Fluency in English is mandatory due to interactions with customers and team members in the USA.

Benefits:

• Opportunity to work at the cutting edge of biotechnology and contribute to innovative solutions in proteomics.
• A collaborative and diverse team environment where ideas are valued and critical feedback is encouraged.
• The chance to make a meaningful impact in the world by improving early disease detection through advanced data analysis.
• A growth-oriented culture that emphasizes personal and professional development in both technical and soft skills.