Signature Science, LLC
  • - TX-Austin
  • Austin, TX, USA
  • Full Time

Position Purpose:   

The successful candidate will support projects related to public safety, defense and national security The data scientist will work collaboratively with teams of software, application, and database developers, statisticians, chemists, physicists, engineers, and other domain experts to design and deliver machine learning data- solutions for our customers, with a focus on enhancing the credibility and defensibility of national and homeland security programs.


Essential Duties and Responsibilities:

  • Collaborate with science, engineering, and business development teams to design and build data interpretation solutions, to include machine learning models, novel data visualizations, image classification, analysis tools and algorithms
  • Develop, document and/or implement application/program testing and validation
  • Design and implement software modules and interfaces among applications or databases
  • Analyze data sets, ranging from sparse datasets to large data and/or unstructured datasets, in order to extract insights, and drive further research opportunities
  • Document, summarize, and present findings to customers, subject matter experts, and other data scientists
  • Research, design, implement, and deploy full-stack scalable computer vision, deep learning, and machine learning solutions to novel problems
  • Keep up with state-of-the-art methods in deep learning and apply them to improve and create new solutions


Required Knowledge, Skills & Abilities:

  • Experience designing and implementing data interpretation approaches to address complex questions, with a preference for experience with scientific questions
  • Experience developing data visualizations to facilitate interpretation and data insights
  • Experience in the use of statistical and predictive modeling concepts, machine-learning approaches, clustering and classification techniques, and optimization algorithms
  • Experience with supervised and unsupervised machine learning algorithms, and ensemble methods, such as: K-Means, PCA, Regression, Neural Networks, Decision Trees, Gradient Boosting
  • Experience with machine learning/deep learning tools or frameworks such as Scikit learn, XGBoost, Spark, Tensorflow, Keras, or PyTorch
  • Technical fluency; comfortable understanding and discussing architectural concepts and algorithms, assessing tradeoffs and new opportunities with technical team members
  • Experience communicating data insights and presenting concepts to technical and non-technical audiences
  • Scientific background (with a focus on chemistry or biology) and/or experience with CBRNE applications preferred
  • Motivated to contribute in a team environment and collaborate across scientific and technical disciplines
  • Able to balance multiple on-going tasks while operating efficiently and with minimal supervision




  • Bachelor Degree (or higher) in computer science, math, software engineering, statistics, data science, or related technical field
  • Proficient in at least one programming language, with preference for R, Python, Javascript, C, C#, C++
  • At least two years, and preferably five+ years, of direct experience with machine learning, data processing, data evaluation, computer science, statistical science and/or software engineering.


Certificates and Licenses:


 None required




Candidate must be able to obtain a Secret level security clearance.


Supervisory Responsibilities:




Working Conditions/ Equipment:

  • Ability to work in varying conditions to include: traditional office environments with sedentary extended periods required for voluminous data analysis via office automation;



The above job description is not intended to be an all-inclusive list of duties and standards of the position.  Incumbents will follow any other instructions, and perform any other related duties, as assigned by their supervisor.







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