Data Analyst – Customer Data Analysis (Spectroscopy)

About nirrin

nirrin is developing sensors and analytics to enable the next generation of biological manufacturing. Using near-infrared spectroscopy we are able to attain real-time, reliable measurements of critical bioprocess parameters. We are primarily focused on applications within the biopharma industry however our technology has the potential to be used across the life sciences.

Our small but passionate team is currently working on integrating novel near-infrared sensors with other data sources to provide process control for cell culture. We are looking for a developer to join our software team and contribute to our data acquisition and analytics software.

About the role

We are seeking a skilled and detail-oriented Data Analyst with a strong background in Python and numerical methods to join our team. The successful candidate will work on analyzing customer data related to spectroscopy, utilizing advanced mathematical and computational techniques. This role requires a deep understanding of Python libraries such as SciPy and NumPy, and experience with minimization/optimization methods to derive actionable insights from complex datasets.

The ideal candidate will have academic experience in numerical methods, particularly courses similar to Harvard’s Applied Math 201, 202, and 205, or equivalent.

Data Analysis and Interpretation:

• Perform advanced data analysis on customer data related to spectroscopy, including signal processing, spectral analysis, and noise reduction.
• Apply statistical methods and machine learning techniques to identify patterns, trends, and correlations in complex datasets.
• Develop and validate models to interpret spectroscopic data, contributing to the understanding of material properties, chemical compositions, or other related applications.

Python Programming:

• Develop, maintain, and optimize Python scripts using libraries such as SciPy, NumPy, pandas, and specialized libraries for spectroscopy data analysis.
• Implement and utilize minimization and optimization algorithms for data fitting, parameter estimation, and other relevant tasks.
• Collaborate with software engineers and data scientists to integrate analysis tools into existing or new data pipelines.

Numerical Methods and Optimization:

• Utilize numerical methods, including but not limited to, numerical integration, differentiation, interpolation, and solving differential equations as applied to spectroscopy data.
• Implement optimization techniques (e.g., gradient descent, least squares fitting) to solve complex data problems and refine data analysis processes.

Customer Data Analysis:

• Interpret and analyze customer data to support strategic decision-making and enhance customer experience.
• Collaborate with stakeholders to understand customer needs, requirements, and data sources.
• Prepare detailed reports and visualizations to communicate findings and recommendations to both technical and non-technical audiences.

Continuous Improvement:

• Stay current with the latest developments in data analysis, spectroscopy, and numerical methods.
• Propose and implement improvements to existing data analysis methodologies and processes.

Qualifications:

Education:

• Bachelor’s or Master’s degree in Applied Mathematics, Physics, Data Science, Computer Science, or a related field. Advanced coursework in numerical methods (e.g., Harvard Applied Math 201, 202, 205 or equivalent) is highly desirable.

Experience:

• Proven experience in data analysis, preferably in an academic or industrial setting related to spectroscopy or similar fields.
• Proficiency in Python and relevant libraries (SciPy, NumPy, pandas) for data analysis, numerical methods, and optimization.
• Strong experience in numerical methods and mathematical modeling, including experience with optimization techniques and data fitting.

Technical Skills:

• Familiarity with spectroscopy data analysis, including understanding of the principles of spectral measurement and interpretation.
• Experience with data visualization tools (e.g., Matplotlib, Seaborn) and statistical analysis.
• Familiarity with software development practices, version control (e.g., Git), and agile methodologies is a plus.

Soft Skills:

• Strong analytical thinking, problem-solving skills, and attention to detail.
• Ability to communicate complex technical concepts to non-technical stakeholders.
• Effective collaboration skills in a multidisciplinary team environment.

Preferred Qualifications:

• Experience with other programming languages (e.g., R, MATLAB) or data analysis tools.
• Familiarity with cloud computing environments (e.g., AWS, Azure) and big data tools.
• Knowledge of machine learning frameworks and experience applying machine learning to spectroscopy or similar datasets.

What We Offer:

• Competitive salary and performance-based bonuses.
• Opportunity to work on cutting-edge projects in the field of spectroscopy and data science.
• Flexible work hours and remote work opportunities.
• Professional development and growth opportunities, including workshops, conferences, and further education.