Data Scientist - Bioinformatics & Computational Biology

We are looking for a Data Scientist to help us build a DNA nanotechnology-enabled next-generation proteomics platform.

About us

nplex was founded with the purpose of making biology easier to understand. To do this, we are untangling some of the most difficult problems in protein profiling and measurement.

Our team is combining DNA nanotechnology, high-dimensional flow cytometry, laboratory automation, and machine learning to develop the world’s highest throughput proteomic platform: the nELISA. Today, every nELISA ‘unit cell’ is zipping at 300,000 proteins per day. We’re aiming to scale to 1M proteins per instrument.day in the next year. In short, we are trying to do for proteomics what Illumina did for DNA sequencing.

We are building a diverse team of engineers, scientists, and world-changers. We like to break down difficult problems using a first principles approach, leveraging the latest breakthroughs from across the scientific and technological spectrum to drive our mission forward.

About the Role

Proteomic data is key to our vision of the future, and every aspect of our company today is geared towards generating more useful proteomic data. In the lab we are scaling the nELISA to generate higher plex and lower cost proteomic data points, and outside the lab we help our scientific users to leverage nELISA data for their research programs. Our data roadmap includes generating robust bioinformatic pipelines to help customers understand their unique datasets, and in parallel we seek to develop improved internal-facing tools that will let us execute faster in the lab by extracting insights from our nELISA, QC, and manufacturing data on demand.

We are looking for a talented and experienced Data Scientist with a Bioinformatics or Computational Biology background who can lead our data science efforts as we scale our next-generation proteomic platform. Working closely with technologists and scientists at nplex, you will be expected to build new data analysis pipelines that let us decipher nELISA data, including QC data from daily operations. Furthermore, together with our team of software engineers, you will get to implement improvements to our data infrastructure. In short - you will play a key role to spearhead our efforts to "scale n" by making core improvements to our understanding and handling of all aspects of nELISA data.

If you join you will get to:

• Extract meaningful insights from all nELISA datasets generated by the team, build data processing tools to help teammates understand nELISA data, and help us wrangle nELISA data on a daily basis.
• Analyze biochemistry and molecular data from a range of other bioanalytical assays, such as: spectroscopy, protein purification, antibody conjugation, DNA modification, and fluorescent labelling. 
• Leverage your technical expertise to develop new data analysis pipelines.
• Help R&D scientists to design large scale assay optimization campaigns that efficiently probe bioassay parameter space and guide further R&D exploration.
• Collaborate with your R&D, scientific and engineering teammates to identify new technical solutions, and communicate analytical results to support decision-making company-wide.
• Play a key role in building a next-generation proteomics technology from the ground up!

We’re looking for someone who has:

• 3+ years of industry experience building data pipelines from the ground up, or equivalent technical proficiency from an academic setting.
• Engineering or Applied Sciences background (or a related technical field).
• Highly proficient in proteomic tools and their associated methods, in particular you would be an expert on multiple of: immunoassays, nucleic acid amplification, DNA nanoarchitecture and design, separation-based techniques for biological samples and compounds, biophysics / fluorescence, and signal processing.
• Statistical skills including bayesian statistics, sampling methods, mixed models, and other statistical concepts.
• Excellent communication skills (written, verbal, and in a codebase) and an independent problem solver.
• Experience working in a fast-paced startup or academic environment.

Nice to haves:

• Software development and/or software engineering experience.
• Machine learning experience.
• Experience working on multiplexed immunoassay datasets.
• Experience in interacting with Laboratory Information Management Systems (LIMS) and/or quality control (QC) and Quality Management Systems (QMS).

Please apply if you:

• Connect deeply with our mission, ambition and sense of duty. We have a mission that isn’t marketing flash: we developed our technology to better measure biology and discover biomarkers for early detection of diseases. We firmly believe we will be successful in literally eradicating certain diseases by enabling them to be diagnosed earlier. We also believe that our hard work to bring this technology to fruition is our duty not only as scientists and engineers, but also as children and parents.
• Are up for a challenge and want to grow: We are a team of problem-solvers, and we continually put ourselves to the test and go into the unknown. We have a growth mindset, and we rely on each other to give critical and candid feedback to ensure that we can reach our full potential.
• Love cutting-edge biotechnology. The nELISA is a new tool that leverages DNA nanotechnology to generate proteomic data more efficiently than ever before. You get to design the means by which users, and ourselves, work with nELISA data going forward.
• Like to work and communicate within a diverse cross-functional team. You would get to interface with teammates from the Engineering, Ops, and Product teams on a daily basis.
• Want the responsibility of addressing some of our hardest problems. Data is one of our core competencies, and researching and developing improvements to the way we analyze data has a compounding benefit on all other aspects of our company and our customers, most notably the scientists using the nELISA.

Job Location Details:
nplex is headquartered in Montreal, Canada. The majority of our team is based in Montreal and works in a new, shared office/laboratory space with an in-person, but flexible work-from-home, policy. We also have full time Engineering teammates working from Boston, Massachusetts and from the San Francisco Bay Area (Redwood City), California. New teammates in Boston or the SF Bay Area would have the opportunity to work in-person / in a partial remote capacity with their local colleagues, or to remain remote-first, as preferred.