Atmospheric Data Scientist

As an Atmospheric Data Scientist at Tomorrow.io, you will be responsible for conducting innovative research to leverage our satellites in weather forecasting, collaborating across teams to develop and document research at the intersection of satellite meteorology and deep learning, and transitioning research breakthroughs into operational products. Additionally, you'll share your research outcomes through professional presentations and publications, all while playing a crucial role in improving our weather products and delivering skillful forecasts to our customers.

To become an Atmospheric Data Scientist at Tomorrow.io, you need a graduate degree in atmospheric science, meteorology, or a related field, along with a minimum of three years of professional experience with modern (deep) machine learning applications in the geosciences. Experience in working with large meteorological data formats and cloud-based environments is also crucial, along with strong communication skills to effectively present complex findings.

Tomorrow.io fosters a dynamic and collaborative work culture where teamwork is emphasized in both in-house and remote settings. As an Atmospheric Data Scientist, you will be part of an 'one office' environment, promoting the idea that magic happens when people work together. We value flexibility, transparency, and prioritizing individual and company growth, encouraging innovation and a positive atmosphere without the pressure of tracking the hours you work.

The Atmospheric Data Scientist position at Tomorrow.io is hybrid, which means you can enjoy the balance of working from home as well as collaborating with your teammates in the office. This structure promotes both independent work and collaborative opportunities, ensuring you have the best of both worlds while contributing to our groundbreaking projects.

Tomorrow.io is dedicated to the career growth of its employees, including Atmospheric Data Scientists. Each team member has their own personalized career growth path, and the company actively invests in support and training opportunities to help you expand your skill set and advance in your career. The fast-paced environment allows for quick movement and recognition of impact, so your growth is directly tied to the contributions you make.

When answering this question, highlight specific projects where you have applied machine learning techniques to atmospheric data. Discuss the objectives, the methodologies you utilized, and the outcomes of your work. Be sure to mention any relevant frameworks or tools you have experience with, such as TensorFlow or Pytorch, to demonstrate your technical expertise.

In your response, outline your process for taking research findings and collaborating with cross-functional teams to convert them into scalable products. Share any experiences where you have successfully led such transitions and detail the challenges faced, along with how you addressed them. This will show your understanding of operationalization in a practical context.

Discuss your experience with deep learning frameworks like TensorFlow or Pytorch, and provide examples of how you have effectively used them in previous projects. Focus on the results achieved and any specific techniques or architectures you implemented, which illustrates your practical knowledge and skills in this area.

Highlight your communication skills by providing examples of scenarios where you’ve had to distill complex scientific concepts into understandable terms for non-expert audiences. You can discuss your presentation experiences at conferences or during internal meetings, emphasizing your ability to tailor your communication style to suit your audience.

Talk about specific projects or experiences where you have worked with meteorological data formats, detailing the type of data you have handled and the tools you used for processing. This highlights both your technical knowledge and your hands-on experience in dealing with large datasets, which is crucial for the Atmospheric Data Scientist role.

Share your methods for keeping up-to-date with industry trends, such as reading scientific journals, attending workshops, or engaging in online forums. You can also mention any relevant communities or networks you are a part of that enable you to exchange knowledge and stay connected with the latest developments in the field.

Provide a detailed account of a specific project, emphasizing the complexity and the specific challenges you encountered. Discuss the steps you took to address these challenges, the solutions you implemented, and what you learned from the experience. This will showcase your problem-solving skills and resilience under pressure.

Outline your experience using cloud platforms like AWS, GCP, or Azure for machine learning applications. Discuss the projects you worked on that utilized these services, detailing how they facilitated your work, particularly in terms of data processing and model training. This will demonstrate your familiarity with essential tools used in the industry.

Discuss your strategy for managing multiple projects effectively. Share techniques you use to prioritize tasks based on urgency and importance, and give an example of a time you successfully navigated competing deadlines without compromising the quality of your work.

This is your chance to express your passion for weather science and innovative technology. Speak to the company's mission and values that resonate with you and mention how your background and interests align with the goals Tomorrow.io pursues, emphasizing your desire to contribute to pioneering weather technology solutions.