Data Analyst – Customer Data Analysis (Spectroscopy)

Nirrin

Nirrin focuses on developing advanced sensors and analytics to pioneer the next era of biological manufacturing through near-infrared spectroscopy. Primarily serving the biopharma industry, their small but dedicated team seeks a developer to enhance their data acquisition and analytics software. This role is crucial for integrating novel near-infrared sensors with other data sources to advance process control in cell culture.

In this role you can expect to have the responsibilities:

• Conduct advanced data analysis on customer data related to spectroscopy, including signal processing and spectral analysis.
• Apply statistical methods and machine learning techniques to discern patterns in complex datasets.
• Develop and validate models to interpret spectroscopic data.
• Create and optimize Python scripts using libraries like SciPy, NumPy, and pandas.
• Implement minimization and optimization algorithms for data fitting and parameter estimation.
• Use numerical methods, including integration and differentiation, for spectroscopy data.
• Analyze customer data to support strategic decisions and improve customer experience.
• Collaborate with stakeholders to understand customer needs and data sources.
• Prepare reports and visualizations to communicate findings to technical and non-technical audiences.
• Stay updated with developments in data analysis and spectroscopy, and propose process improvements.

This role comes with the following benefits:

• Competitive salary and performance-based bonuses.
• Opportunity to work on innovative projects in spectroscopy and data science.
• Flexible work hours and remote work options.
• Professional development opportunities including workshops and conferences.

This role requires you to have:

• Bachelor's or Master's degree in Applied Mathematics, Physics, Data Science, Computer Science, or related field.
• Experience in data analysis, especially in spectroscopy.
• Proficiency in Python and libraries such as SciPy, NumPy, and pandas.
• Deep understanding of numerical methods and mathematical modeling.
• Experience with data visualization tools like Matplotlib and Seaborn.

You would benefit from having:

• Experience with other programming languages like R or MATLAB.
• Familiarity with cloud computing environments like AWS or Azure.
• Knowledge of machine learning frameworks and applications in spectroscopy.

This role adheres to the federal Transparency in Coverage Rule, providing machine-readable files for easier data access and analysis by researchers and regulators.