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Senior Data Scientist 219 views

Job Description

 

Tomorrow.io’s Weather department is a mixture of scientists and engineers committed to generating the best and most novel data and models across all times: historical, real-time and forecast. We also focus on making everything become a weather station (from cars to microwave links to IoT devices). The story just begins when the data hits our ingest and post-processing services. Every product that the user sees is the result of a pipeline of algorithms that needs to be run quickly and continuously. We are the team that builds the architecture behind the data and the models, to prepare the weather analyses, for the Product and Engineering team to serve to the masses.

We’re looking for a Senior Data Scientist with a Meteorological background to have a dual role. Lead internally the data pipelines for the ML applications of Tomorrow.io and have also a client-facing role, to work in a fast-paced Agile development environment for modernizing science-driven applications to operate on cloud platforms.  Our team provides acceleration of community-developed scientific and technological enhancements into the operational applications for Numerical Weather Prediction (NWP) and improved Research to Operations (R2O). As a member of the team, you will ensure adherence to operational agreements and policies (including response times), compliance to program and customer standards and requirements (including Section 508 compliance), leveraging of industry best practices for automation and scalability of assets, and implementation of issue detection and alerts.

As a Senior Data Scientist at Tomorrow.io you’ll:

  • Working on an agile team to support the development of prototypes and operational systems, starting with the UFS-Atmospheric River (UFS-AR) Application.
  • Analyze, process, and model metadata then interpret the results to create actionable plans.
  • Implement FAIR principles on the datasets.
  • Define and implement machine learning algorithms against the collected data.
  • Gather and analyze large sets of structured and unstructured UFS data to determine data organization trends.
  • Provide EPIC community best practices on data structure, based on UFS code and data types, using real-time sessions and screen sharing and other duties as assigned.

What you bring:

  • 8 years of relevant experience with a BS degree in Meteorology, Data Science, Computer Science, or an IT related field preferred (Optionally STEM focused – Science, Technology, Engineering or Mathematics with relevant work experience around the required skills below)
  • Experience with cleansing data to discard irrelevant information and prepare the data for preprocessing and modeling.
  • Experience discovering new algorithms for solving problems and building programs to automate recurring tasks.
  • Excellent verbal and written communication skills. Good experience in preparing IT technical documents.
  • Knowledge of data analytics, with at least 1 year of experience using Machine Learning (ML)/ Artificial Intelligence (AI) for data mining, data visualization, and reporting.
  • Experience using programming languages such as Fortran and Python in an Agile environment.
  • At least 1 year of solving business problems through undirected research and framing open-ended industry questions.
  • At least 1 year of extracting huge volumes of structured and unstructured data, using SQL and web scraping/APIs, respectively.

If you’re seeking an opportunity to work with cutting-edge technology in weather forecasting and contribute significantly to enhancing climate change security, then this is the ideal place for you!

If your experience is close but doesn’t fulfill all requirements, please apply. Tomorrow.io is on a mission to build a special company. To achieve our goal, we are focused on hiring people with different backgrounds, perspectives, and experiences.Tomorrow.io is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran, or disability status.

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