Associate Scientist, Data

3 weeks ago

Mountain View, United States Universities Space Research Association Full time
Job DescriptionJob DescriptionThe Universities Space Research Association (USRA) has a mission to advance space-related sciences and exploration through innovative research, technology, and education programs that involve universities, governments, and the private sector for the benefit of humanity. As part of this mission, USRA is conducting collaborative research for exploring emerging technologies such as artificial intelligence (AI), machine learning (ML), and data analytics for enhancing space exploration capabilities and scientific discoveries. As an Associate Data Scientist, you will be part of our dynamic data science team, contributing to the development and deployment of data-driven solutions across various business areas. You will collaborate with senior data scientists, analysts, and stakeholders to extract actionable insights from complex datasets, build predictive models, and help drive data-centric decision-making within the organization. The Associate Scientist will engage in research, development, and implementation, encompassing a wide range of projects including but not limited to real-world use cases for natural hazards monitoring and prevention. Successful candidates will have experience in machine learning, statistics, and data visualization, along with strong programming skills in Python and C++.

Essential Duties/Responsibilities:
  • Conduct research to understand and identify patterns in large datasets related to natural hazards.
  • Develop and implement machine learning models for predictive analysis and risk assessment.
  • Collaborate with cross-functional teams to design and deploy data-driven solutions.
  • Evaluate model performance and iterate on algorithms to improve accuracy and efficiency.
  • Communicate findings and insights to stakeholders through reports, presentations, and data visualizations.
  • Stay updated with the latest advancements in data science, machine learning, and related technologies.
  • Participate in brainstorming sessions and contribute innovative ideas for solving complex problems.
  • Document processes, methodologies, and code to ensure reproducibility and knowledge sharing within the team.
  • Support the development of data infrastructure and tools to streamline data collection, storage, and analysis.

Additional Responsibilities:

  • Collaborate with domain experts to understand the specific requirements and nuances of real-world data.
  • Assist in the development of data pipelines and workflows for efficient data preprocessing and feature engineering.
  • Conduct exploratory data analysis (EDA) to uncover trends, anomalies, and potential areas for further investigation.
  • Participate in code reviews, peer discussions, and knowledge sharing sessions to foster a collaborative and learning-oriented environment.
Required Qualifications:

Education:
  • A Master’s Degree or higher in, Computer Science or related field. PhD preferred.
Experience
  • Minimum 5+ years developing scientific models and performing analyses
  • Minimum 2-5 years managing and completing complex, multi-faceted scientific projects
Knowledge, Skills & Abilities:
  • Strong understanding of machine learning algorithms such as regression, classification, clustering, and ensemble methods.
  • Strong understanding of advanced machine learning techniques such as transformers, and generative artificial intelligence approaches.
  • Proficiency in statistical analysis and hypothesis testing techniques.
  • Knowledge of data preprocessing techniques including data cleaning, transformation, and normalization.
  • Proficient programming skills in Python and C++ for data analysis, modeling, and software development.
  • Experience working with data manipulation libraries such as Pandas, NumPy, and SciPy.
  • Ability to develop and deploy machine learning models using frameworks like TensorFlow, PyTorch, or scikit-learn.
  • Strong problem-solving skills with the ability to approach problems from a quantitative and analytical perspective.
Working Conditions:

Work will be performed in an office environment. While performing the duties of this job, the employee is frequently required to stand, walk, sit, talk, or hear.

Travel:

Employee must be willing and able to travel. Position may require limited domestic and international business travel.

NO RELOCATION

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