Our client develops specialized industrial process analyzers based on spectroscopy analysis for a variety of industries including pharmaceutical development and manufacturing, production of petrochemicals, chemicals and polymers, drinking water processing/wastewater treatment, and more.
Beginning with an initial analysis of a market-driven problem, our client develops solutions for the collection of quality data, powerful predictive analytics, knowledge-extraction, and ending with a semi-automated decision-support system that results in high-throughput spectroscopy analytics.
An ideal candidate for this role might be a data analyst with experience in pattern recognition. Another possibility might be an engineer with scientific software experience and an interest in data analysis. In any case, this individual will need to be someone who is highly interested in engineering and producing tangible products to go to market.
Ann Arbor, MI
Compensation is dependent upon level of education and experience, up to 140K.
Purely academic experience may be considered.
Minimum four-year degree in a discipline such as Chemistry, Physics, Mathematics, Data Science or Software/Computer Science, Predictive Analytics, Machine Learning, Artificial Intelligence or Computer Vision.
Master's or PhD in one of the above categories preferred, but not required.
- Highly skilled in advanced data analytics, pattern recognition, machine learning, AI (neural nets, deep learning, supervised and unsupervised machine learning approaches) or a related discipline
- Familiarity with approaches and techniques like Design Of Experiment (DOE), noise analysis and filtering, Principal Component Analysis (PCA) and Partial Least Squares (PLS)
- Significant experience in solving challenging design and data-analytic problems
- Interested in a role involving initial analysis of a market-driven problem, developing appropriate methods needed to enable the collection of quality data, powerful predictive analytics, knowledge-extraction, and ending with semi-automated decision-support systems
BENEFICIAL BUT NOT REQUIRED
- Basic understanding of spectroscopic methods, separation technology analyzers, and vibrational spectroscopy
- Familiarity with chemometrics
- Management experience of a product team (hardware, software, data, technical services or similar)
- This is a lead role in the engineering department which will grow to supervise 3-5 engineers
- In this role you will develop spectral analysis algorithms and approaches, data-science protocols, and machine learning decision support systems.
- Although there is a significant amount of research and gaining fundamental understanding, the primary objective is the creation of salable instrumentation and software as quickly and efficiently as possible.
- This opportunity offers significant advancement potential