Data Scientist Job at ConSol Partners, Austin, TX

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  • ConSol Partners
  • Austin, TX

Job Description

Data Scientist

Role Overview

A skilled Data Scientist is sought to join the team and play a critical role in defining and evaluating the performance metrics of autonomous vehicle systems. The individual will be responsible for designing and implementing quantitative measures to assess driving behavior, safety compliance, and passenger comfort. This role involves analyzing large datasets, applying advanced statistical methods, and collaborating with cross-functional teams to ensure the autonomous systems meet the highest standards for safety and reliability. The position offers an opportunity to significantly impact the future of autonomous driving technology.

Key Responsibilities

  • Analyze real-world and simulated data from autonomous vehicle experiments to assess system performance.
  • Develop and optimize quantitative metrics (both rule-based and machine learning-driven) to evaluate driving behavior, safety, and passenger comfort.
  • Apply statistical techniques, such as hypothesis testing and inference, to validate the reliability and sensitivity of metrics.
  • Collaborate with autonomy software, simulation, and safety teams to identify areas for improvement based on data-driven insights.
  • Build scalable data pipelines to automate the calculation and reporting of performance metrics.
  • Review driving logs and participate in test rides to validate data analyses against real-world conditions.
  • Qualifications 2+ years of experience in data science, applied statistics, or metrics development.
  • Proficiency in Python and SQL for data manipulation and analysis.
  • Strong foundation in statistical methods (e.g., A/B testing, regression, confidence intervals).
  • Experience in designing metrics to evaluate complex systems (e.g., robotics, autonomous systems, or large-scale software).
  • Ability to effectively communicate technical findings to cross-functional stakeholders.

Preferred Skills

  • Experience with machine learning, including model evaluation and feature engineering.
  • Familiarity with big data technologies (e.g., Spark, Hadoop, MapReduce).
  • Knowledge of traffic regulations and automotive safety standards (e.g., NHTSA guidelines).

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