Nucleix is a leader in the field of next-generation sequencing and its application in medical diagnostics. Our commitment to research and technology in this area is foundational to our mission.
Nucleix is at the forefront of advancing medical diagnostics. Our innovative assay technology is contributing to new standards in lung cancer screening, aiming towards a future where early detection is the norm, not the exception. Our mission, while ambitious, has a deeply meaningful impact. We aim to detect lung cancer at its earliest stages with just a single tube of blood, striving to make healthcare more accessible to all. The journey at Nucleix is not only about the blend of rigorous science and novel technology in our assay, but also about our dedicated team members who are committed to changing the course of lung cancer diagnosis.
As we progress, we are in search of a Staff Data Scientist to play a pivotal role in this significant mission. You will be part of efforts centered around groundbreaking medical innovations, contributing tangibly to the global fight against lung cancer. The work, while demanding, is immensely rewarding with every project aimed at exploring the extents of what's achievable in cancer screening.
You have a solid mathematical foundation and adeptness in deploying the machine learning techniques. You know a solid foundation in standard machine learning workflows, from EDA to model selection, tuning and implementation. You have built deep learning models from the ground up as well as fine tuned publicly available models successfully to solve real life problems. You have sufficient knowledge and organizational skills to mentor and develop a team of talented data scientists / data analysts.
At Nucleix, you'll immerse yourself in a stimulating environment alongside some of the brightest minds in the field. Our team is a hub of innovation, each member contributing a wealth of expertise and a relentless drive for exploration and excellence. In our culture of open collaboration and continuous learning, every voice is valued. The accessibility of senior management, including the CEO, fosters a conducive environment for sharing ideas and insights. Your contributions will not only be recognized but will play a critical role in advancing our mission, making a lasting impact in the global fight against lung cancer.
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Key Responsibilities:
Lead and oversee data science projects, with a focus on NGS data analysis.
Contribute to strategic decision-making and high-level planning in relation to NGS data projects.
Solve complex problems and innovate in the analysis and interpretation of NGS data.
Spearhead the creation and implementation of AI and ML strategies and algorithms aimed at identifying markers and marker panels for future clinical tests.
Innovate and implement effective data visualization techniques for both internal and external stakeholders.
Conduct ad-hoc data analyses to glean critical insights that propel our mission forward.
Champion projects from inception through to implementation, ensuring alignment with defined requirements and seamless integration.
Collaborate closely with cross-functional teams (Software, Research, Product Development, Clinical) to understand project requisites and drive implementation.
Ensure projects are on schedule, meet defined requirements, and are well-documented in compliance with Nucleix's Quality Management System.
Qualifications:
- Minimum of 10 years of experience in data science, with substantial experience in next-generation sequencing (NGS) data analysis (minimum of 5+ years with PhD degree.
- Demonstrated ability to lead projects and teams, particularly in NGS data analysis or related fields.
- Advanced skills in statistical analysis, machine learning, and bioinformatics, specifically related to NGS.
PhD. in Computer Science / Mathematics / Bioinformatics / Statistics or related fields
MSc. Candidates with extensive experience and knowledge will also be considered.
5+ years' industry experience as a data scientist / bioinformatician working on biological data
Proven expertise in developing machine learning models with a strong statistical foundation
Expert level knowledge in Python
Fluid in the main data science tools (i.e. scikit-learn, SQL, Tensorflow, )
Experience with using and setting up a ML Ops pipeline (for example ML Flow)
Solid knowledge of cloud environments such as Amazon's AWS
Experienced in deploying produciton-level ML in cloud environments such as GCP, AWS, Azure, etc.
Expertise in NGS data or equivalent molecular experience
Proven experience" in collaborating and communicating effectively across multidisciplinary teams..
Exceptional organizational skills with a keen eye for detail.
Experienced in working in collaborative data science environment with tools such as Git, docker, etc.