Data Scientist, Data Platform

Noetik

1d•Hybrid

About The Position

The Data Scientist will build and productionize scientific data pipelines for large-scale scientific datasets, particularly imaging and multimodal data, and develop methods for image and scientific data processing. The role owns software and pipelines from initial development through production deployment, operation, and ongoing improvement. It also involves designing metadata schemas, data models, and programmatic interfaces that make scientific datasets understandable, queryable, versioned, and useful to downstream users. The position works across software engineering, machine learning research, and scientific teams to integrate new data types into Noetik’s data platform. The Data Scientist will create reusable tools and libraries, improve processing workflows for correctness, scalability, reproducibility, and efficiency, and use distributed computing and cloud infrastructure to process large datasets. Modern AI coding tools and agents are part of the engineering workflow.

Requirements

Strong Python programming skills and the ability to build high-quality, maintainable software beyond notebooks and exploratory analysis.
Experience developing data processing, scientific computing, image processing, or computational pipelines used and relied upon by others.
Strong understanding of data modeling, relational databases, metadata, schemas, dataset versioning, and reliable data access for downstream users.
Experience with image processing, computer vision, microscopy, medical imaging, remote sensing, or other large-scale image datasets.
Strong quantitative and computational problem-solving skills, including the ability to evaluate unfamiliar datasets and identify appropriate processing and validation approaches.
Experience writing tested, reusable, production-quality software and following standard engineering practices, including version control, code review, and automated testing.
Ability to learn quickly and navigate problems spanning data science, software engineering, and scientific computing.
Comfort using AI coding tools and agents as a core part of development while maintaining high standards for correctness, maintainability, and understanding.
Collaborative, low-ego approach focused on solving problems as a team and finding the best solution.

Nice To Haves

Experience developing image processing methods for registration, segmentation, normalization, feature extraction, or image quality control.
Experience with large-scale or distributed data processing using Ray, Dask, Spark, or similar frameworks.
Experience with PostgreSQL, AWS, cloud object storage, or modern data platform technologies.
Experience integrating machine learning models into scientific or image processing pipelines.
Experience working with biological, biomedical, or other complex scientific datasets.
Background in biotech, pharma, scientific computing, medical imaging, industrial imaging, or another technically rigorous, data-intensive environment.

Responsibilities

Develop robust Python-based pipelines to process, transform, validate, and organize large-scale scientific datasets, particularly imaging and multimodal data.
Create image and scientific data processing methods for normalization, registration, segmentation, feature extraction, quality control, and dataset-specific transformations.
Own end-to-end software development, from initial pipeline development through production deployment, operation, and continuous improvement.
Design metadata schemas, data models, and programmatic interfaces for understanding, querying, versioning, and using scientific datasets.
Collaborate with software engineers, ML researchers, and scientific teams to determine how new data types should be processed and integrated into the data platform.
Develop reusable tools and libraries that apply processing methods consistently and efficiently across large datasets.
Improve data processing workflows for correctness, scalability, reproducibility, and efficiency.
Use distributed computing and cloud infrastructure to support computationally intensive processing across large datasets.
Use AI coding tools and agents to accelerate implementation, debugging, analysis, testing, exploration, and maintenance.

Benefits

Generous health, dental, and vision insurance, with premiums fully covered for employees and dependents depending on plan choice.
HSA and FSA accounts.
Dependent care savings.
Employee assistance program and mental health resources.
Health care navigation and advocacy.
Flexible PTO.
Nine paid holidays.
Two full-week synchronized company breaks, plus the Friday after Thanksgiving.
Competitive base salary.
Stock options.
401(k) plan with employer match.
Fully covered disability, life, and AD&D insurance.
Generous parental leave.
Optional pet insurance, legal services, and identity theft protection programs.
Daily catered lunches for team members working onsite.