Description:

Invert is on a mission to reduce the cost and time of using biology for manufacturing.
The company provides tools for automating the design, execution, and analysis of bioprocessing.
The Data Science team is focused on groundbreaking applied research solutions in bioprocessing.
As a Staff Data Scientist, you will lead the development of models and algorithms specific to bioprocess data.
Responsibilities include selecting and applying appropriate models, preparing datasets, and identifying opportunities for foundational model development.
The role involves hands-on work, producing reproducible and well-documented research, and delivering models that enhance speed and product for customers.

Requirements:

Exceptional problem-solving skills and a deep understanding of data science methodologies are required.
Candidates must be intrinsically motivated and driven to succeed.
A track record of leadership and vision in the bioprocess industry, including published research, is necessary.
Effective communication skills are essential to ensure timely information dissemination.
Candidates should demonstrate innovation by bringing new ideas to improve bioprocess outcomes.
Taking ownership and accountability for team success is a must.
Proficiency in time series forecasting, optimization, neural networks, feature engineering, statistical techniques, linear algebra, hybrid modeling, fluid dynamics, adaptive experimentation, and Bayesian methods is required.
The ability to deliver high-quality results with a focus on velocity is essential.
Candidates must act in the company’s best interests and be trustworthy.

The position offers the opportunity to work in a high-growth startup with impactful work.
It is a fully remote role, with team members distributed across US and European timezones.
Competitive salary, equity, and benefits are provided.
New laptop, monitor, and accessories of your choice will be supplied.
Frequent team off-sites are organized to foster collaboration.
Unlimited paid time off (PTO) is offered to employees.