Die KI-Suchmaschine für Jobs
Biology Data Quality Engineer(m/w/x)
Beschreibung
You will ensure the integrity of complex biological datasets by building automated validation pipelines and standardizing data, playing a vital role in training foundation models.
Lass KI die perfekten Jobs für dich finden!
Lade deinen CV hoch und die Nejo-KI findet passende Stellenangebote für dich.
Anforderungen
- •Team-first attitude and independence
- •Curiosity and detail-orientation
- •Ability to thrive in dynamic environments
- •Strong domain expertise in biology
- •Strong computational and hands-on skills
- •Deep understanding of transcriptomics data
- •Knowledge of genomics and proteomics data
- •Experience in data quality control
- •Familiarity with data validation tools
- •Strong analytical and problem-solving skills
- •Proficiency in Python
- •Knowledge of data visualization libraries
- •Excellent written and verbal communication
- •MSc in Biology, Computational Biology, or Bioinformatics
- •Experience in machine learning for histology
- •Experience working with AWS
- •Experience with data annotation guidelines
- •Experience with data ontologies
- •Experience building large-scale data collections
- •Experience in spatial alignment of datasets
Ausbildung
Berufserfahrung
ca. 1 - 4 Jahre
Aufgaben
- •Develop comprehensive data validation protocols for histology, omics, and clinical datasets
- •Design automated pipelines to streamline data validation and identify issues early
- •Establish data standardization practices for seamless integration across different data types
- •Curate biological datasets to enhance their usability for machine learning
- •Collaborate with the R&D team to address specific data quality requirements
- •Communicate findings and recommendations to technical and non-technical stakeholders
- •Coordinate and synchronize data standards with external providers
- •Document quality assessment procedures, validation results, and data specifications
- •Generate regular reports on data quality metrics and trends
- •Evaluate external public data sources for foundation model training suitability
- •Implement improvements to data quality processes based on industry best practices
Tools & Technologien
Sprachen
Englisch – verhandlungssicher
Benefits
Flexibles Arbeiten
- •Flexible work arrangements
- •Remote work options
Attraktive Vergütung
- •Competitive salary
- •Equity package
Karriere- und Weiterentwicklung
- •Professional growth opportunities
- •Leadership development opportunities
Sinnstiftende Arbeit
- •Collaborative and mission-driven environment
- Makersite GmbHVollzeitRemoteBerufserfahrenBerlin
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Biology Data Quality Engineer(m/w/x)
Die KI-Suchmaschine für Jobs
Beschreibung
You will ensure the integrity of complex biological datasets by building automated validation pipelines and standardizing data, playing a vital role in training foundation models.
Lass KI die perfekten Jobs für dich finden!
Lade deinen CV hoch und die Nejo-KI findet passende Stellenangebote für dich.
Anforderungen
- •Team-first attitude and independence
- •Curiosity and detail-orientation
- •Ability to thrive in dynamic environments
- •Strong domain expertise in biology
- •Strong computational and hands-on skills
- •Deep understanding of transcriptomics data
- •Knowledge of genomics and proteomics data
- •Experience in data quality control
- •Familiarity with data validation tools
- •Strong analytical and problem-solving skills
- •Proficiency in Python
- •Knowledge of data visualization libraries
- •Excellent written and verbal communication
- •MSc in Biology, Computational Biology, or Bioinformatics
- •Experience in machine learning for histology
- •Experience working with AWS
- •Experience with data annotation guidelines
- •Experience with data ontologies
- •Experience building large-scale data collections
- •Experience in spatial alignment of datasets
Ausbildung
Berufserfahrung
ca. 1 - 4 Jahre
Aufgaben
- •Develop comprehensive data validation protocols for histology, omics, and clinical datasets
- •Design automated pipelines to streamline data validation and identify issues early
- •Establish data standardization practices for seamless integration across different data types
- •Curate biological datasets to enhance their usability for machine learning
- •Collaborate with the R&D team to address specific data quality requirements
- •Communicate findings and recommendations to technical and non-technical stakeholders
- •Coordinate and synchronize data standards with external providers
- •Document quality assessment procedures, validation results, and data specifications
- •Generate regular reports on data quality metrics and trends
- •Evaluate external public data sources for foundation model training suitability
- •Implement improvements to data quality processes based on industry best practices
Tools & Technologien
Sprachen
Englisch – verhandlungssicher
Benefits
Flexibles Arbeiten
- •Flexible work arrangements
- •Remote work options
Attraktive Vergütung
- •Competitive salary
- •Equity package
Karriere- und Weiterentwicklung
- •Professional growth opportunities
- •Leadership development opportunities
Sinnstiftende Arbeit
- •Collaborative and mission-driven environment
Über das Unternehmen
Bioptimus
Branche
Research
Beschreibung
The company is building the first universal AI foundation model for biology to fuel breakthrough discoveries and accelerate innovation in biomedicine.
- Makersite GmbH
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Vollzeitmit HomeofficeBerufserfahrenBerlin - DeepL
Senior Research Data Engineer(m/w/x)
Vollzeitmit HomeofficeSeniorBerlin - Clue
(Senior) ML Engineer(m/w/x)
Vollzeitmit HomeofficeSeniorBerlin