Slingshot Aerospace

Sr. Data Scientist

Remote US
USD 155k - 190k
C++ Deep Learning Machine Learning Julia Python Java Kotlin
Description

What You’ll Do:

In this role, you will be a member of the Data Science team, which is rooted within the larger science organization at Slingshot.  You will contribute directly to Slingshot’s vision to accelerate space sustainability to create a safer, more connected world. 

Slingshot Aerospace cares deeply about our commitment to company values, mission, and purpose. The core competencies we will be looking to identify include intellectual agility, ability to develop innovative solutions, leadership, performance orientation, and industry expertise.

Position Responsibilities: 

  • Development of machine learning approaches, algorithms, and prototypes that lend datasets and scenario insights into key business arenas and future opportunities
  • Create and prepare predictive models into Slingshot data science software products
  • Identify and design data science product development, business concepts, and outreach activities
  • Build and refine simulation-based dataset development, research, insights, and predictions
  • Participate in a strong matrixed data science team and culture
  • Identify, lead, and deliver data science modeling insights as publications, papers, internal communications, and patents
  • Perform other duties as assigned (to be less than 10% of the responsibilities listed above)

 

Pre-Requisites

  • Must be eligible to obtain or maintain US Government Security Clearance

 

Minimum Requirements

  • Advanced degree (Ph.D. or MS plus 2 years experience) with graduate degree in mathematics, data science, physics, or other related quantitative discipline
  • Conducted quantitative research with an emphasis in one or more of the following areas: (a) simulation modeling and analysis, (b) reinforcement learning, (c) agent-based modeling, prediction, and insights, or (d) stochastic data set construction
  • Demonstrated proficiency in algorithm development and implementation in one or more formal programming language(s) (e.g. Julia, Python, java/kotlin, C/C++)
  • Expert-level understanding of machine learning and deep learning
  • Ability to work within multi-disciplinary teams in a fast-paced, evolving operational environment that spans military, government, and industry partners
  • Excellent verbal and written communication skills

 

Preferred Skills

  • Published peer-reviewed journal articles employing data science simulation methods, approaches, applications, predictions, or dataset creation
  • Experience with aerospace and astrodynamics research or subject areas
  • Ability to demonstrate creative solutions to challenging projects 
  • Development of AI algorithms for use in environmental, physical, or behavior prediction
  • Experience leading the development, implementation, and transition of technology to production

These skills are guidelines, not hard and fast rules. You don’t have to meet every qualification listed - if your skills are transferable and you meet the minimum requirements, we encourage you to apply. 

Location: Remote, US

Classification: Full-time Exempt

Compensation: $155,000 - $190,000 annually

We are currently only able to hire residents of the following U.S. states: AZ, CA, CO, DC, FL, GA, HI, IL, IN, KS, MD, MA, MI, MN, MO, MT, NV, NM, NY, NC, OR, RI, TN, TX, UT, VT, VA, WA, WV, and WI. We are unable to consider candidates residing in other U.S. states at this time.

Equity, Diversity & Inclusion are key to our success. We are an Equal Opportunity Employer and our employees are people with different strengths, experiences and backgrounds, who share a passion for creating a safer, more connected world. Diversity not only includes race and gender identity, but also age, disability status, veteran status, sexual orientation, religion and many other parts of one’s identity. All of our employee’s points of view are key to our success, and we embrace individuality.

Slingshot Aerospace
Slingshot Aerospace
Aerospace Analytics Artificial Intelligence Geospatial Machine Learning

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