R&I Scientist - Data Analyst

Job Expired

PARIS, France

Full Time

8 months ago

Job description

Interstellar Lab is a groundbreaking company at the forefront of biology, AI, and space exploration. Our mission is to harmonize advanced technology with ancient agricultural wisdom to cultivate plants on Earth and in Space. We specialize in optimizing the growth and composition of a diverse range of high-value plants, including medicinal, cosmetic, food, and tropical varieties.

Position Overview:

We are seeking an adaptable and highly skilled Research & Innovation (R&I) Scientist with an interdisciplinary background encompassing both scientific research and data analysis. This individual will play a crucial role in automating analytical processes, collecting, formatting, and analyzing data to drive insights, and ensure the success of our plant cultivation projects. Candidates with a background in data analysis or data science are encouraged to apply.

Key Responsibilities:

  • Automate and optimize analytical processes to enhance efficiency and reliability in plant growth experiments.
  • Collect, format, and organize data from various sources, including sensors, experiments, and simulations.
  • Utilize data analysis and visualization tools to derive actionable insights and support decision-making.
  • Collaborate with our plant scientists and researchers to understand the data needs for ongoing projects and provide analytical support.
  • Develop and implement data-driven algorithms to improve plant growth conditions and sustainability.
  • Contribute to the design of experiments and data collection methodologies.
  • Assist in the development of predictive models for plant growth and environmental impact.
  • Collaborate with interdisciplinary teams on various research projects related to sustainable agriculture and space exploration.

Basic Qualifications:

  • Master's degree (MSc) in a relevant scientific field, chemistry, data science, or data analysis.
  • Strong interdisciplinary background with a combination of scientific research and data analysis skills.
  • Proficiency in data analysis tools and programming languages (e.g., Python).
  • Experience with data visualization and statistical analysis.
  • Excellent problem-solving skills and attention to detail.
  • Strong communication and collaboration abilities.
  • Ability to adapt and learn quickly in a dynamic research environment.

Preferred Skills and Experience:

  • Prior experience in plant science, controlled environment agriculture, or a related field.
  • Familiarity with experimental design and statistical analysis.
  • Knowledge of machine learning and predictive modeling techniques.
  • Experience with automation tools and hardware.

Location:

This position is based in Paris, France, with occasional travel to our site at NASA Kennedy Space Center in the United States.

Compensation and Benefits:

Your compensation package, including base salary, will be determined based on your qualifications, experience, and knowledge. In addition to your base salary, you may be eligible for long-term incentives, such as company stock or stock options. Interstellar Lab offers comprehensive medical, vision, and dental coverage, a 401(k) retirement plan, short and long-term disability insurance, life insurance, paid parental leave, and various other discounts and perks.

Interstellar Lab is proud to be an equal opportunity employer and values diversity in its workforce. We do not discriminate on the basis of race, color, national origin, gender, sexual orientation, gender identity, age, disability, or other legally protected characteristics. We are committed to fostering an inclusive and diverse workplace that reflects the global communities we serve.

If you are a dynamic and interdisciplinary R&I Scientist with a passion for data analysis and a desire to contribute to sustainable agriculture and space exploration, we encourage you to apply for this unique opportunity at Interstellar Lab. Join us in our mission to cultivate a better future on Earth and beyond.

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