Autonomous Solutions
Join us at ASI, where we are transforming industries through cutting-edge autonomous robotics solutions that prioritize safety, productivity, and efficiency. Guided by our core values of Simplicity, Safety, Transparency, Humility, Attention to Detail, and Growth, we are excited to shape the future of automation in rapidly evolving markets.
As a Lead Data Scientist, you will be pivotal in advancing ASI's top-tier autonomous systems, turning complex vehicle and operational data into actionable insights. This role focuses on developing reliable and high-performing AI capabilities by creating robust data pipelines and high-quality training datasets, alongside meaningful performance metrics. You will work closely with AI/ML Engineers, Simulation Specialists, and Principal Architects to ensure our autonomy stack is built on a solid, data-driven foundation.
Key Responsibilities:
Analyze both structured and unstructured data from various sources including sensors, vehicle logs, simulations, and field operations to uncover trends, anomalies, and areas for improvement. Utilize field feedback and operational information to generate insights that lead to continuous enhancements in our products and influence technology roadmap strategies. Design and maintain pipelines that facilitate movement between time-series storage and relational models, allowing for advanced analysis and comprehensive reporting. Define and build relational database models to manage and summarize sensor data effectively, supporting ad hoc analysis, ML feature generation, and business reporting. Establish, monitor, and communicate key performance metrics for autonomy systems in collaboration with engineering teams to ensure accountability and alignment. Work jointly with AI/ML Engineers and Simulation Specialists to identify gaps, prioritize labeling needs, and develop synthetic/simulation data strategies. Create and validate data-driven hypotheses to inform system design and R&D decisions related to new autonomy concepts. Set and enforce data quality standards through validation and cleansing processes ensuring reliable inputs for analysis and AI development. Examine real-world deployment data for continuous model improvement and to support closed-loop validation processes. Collaborate with Business Intelligence (BI) teams to align the technology roadmap priorities with application and execution needs, ensuring data models and pipelines effectively support decision-making and reporting. Required Qualifications:
Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Engineering, or a related field. 3-7 years of professional experience in data analysis, data engineering, or applied machine learning, showcasing a significant impact on product development. Experience with time-series databases (e.g., InfluxDB) and relational databases (e.g., Postgres, MySQL, SQL Server), including the ability to craft and execute complex queries. Understanding of relational theory involving schema design and the best practices for organizing analytical models to enhance AI models. Proficient in Python (including libraries such as pandas, NumPy, scikit-learn) and SQL, demonstrating strong skills in data manipulation and analysis. Proven experience in designing and maintaining robust data pipelines that handle large-scale sensor data. Familiarity with data visualization and dashboarding tools such as Power BI is a plus. Solid foundation in statistical analysis, experimental design, and machine learning principles. Exposure to autonomy, robotics, automotive or construction vehicle systems, or sensor data is highly advantageous. At Autonomous Solutions, Inc. (ASI), we promote a diverse, inclusive, and equitable workplace, offering equal opportunities to all employees and applicants. We are committed to preventing discrimination and harassment of any kind, and we comply with all applicable laws related to non-discrimination in employment. We also provide reasonable accommodations for individuals with disabilities throughout the hiring process.
Analyze both structured and unstructured data from various sources including sensors, vehicle logs, simulations, and field operations to uncover trends, anomalies, and areas for improvement. Utilize field feedback and operational information to generate insights that lead to continuous enhancements in our products and influence technology roadmap strategies. Design and maintain pipelines that facilitate movement between time-series storage and relational models, allowing for advanced analysis and comprehensive reporting. Define and build relational database models to manage and summarize sensor data effectively, supporting ad hoc analysis, ML feature generation, and business reporting. Establish, monitor, and communicate key performance metrics for autonomy systems in collaboration with engineering teams to ensure accountability and alignment. Work jointly with AI/ML Engineers and Simulation Specialists to identify gaps, prioritize labeling needs, and develop synthetic/simulation data strategies. Create and validate data-driven hypotheses to inform system design and R&D decisions related to new autonomy concepts. Set and enforce data quality standards through validation and cleansing processes ensuring reliable inputs for analysis and AI development. Examine real-world deployment data for continuous model improvement and to support closed-loop validation processes. Collaborate with Business Intelligence (BI) teams to align the technology roadmap priorities with application and execution needs, ensuring data models and pipelines effectively support decision-making and reporting. Required Qualifications:
Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Engineering, or a related field. 3-7 years of professional experience in data analysis, data engineering, or applied machine learning, showcasing a significant impact on product development. Experience with time-series databases (e.g., InfluxDB) and relational databases (e.g., Postgres, MySQL, SQL Server), including the ability to craft and execute complex queries. Understanding of relational theory involving schema design and the best practices for organizing analytical models to enhance AI models. Proficient in Python (including libraries such as pandas, NumPy, scikit-learn) and SQL, demonstrating strong skills in data manipulation and analysis. Proven experience in designing and maintaining robust data pipelines that handle large-scale sensor data. Familiarity with data visualization and dashboarding tools such as Power BI is a plus. Solid foundation in statistical analysis, experimental design, and machine learning principles. Exposure to autonomy, robotics, automotive or construction vehicle systems, or sensor data is highly advantageous. At Autonomous Solutions, Inc. (ASI), we promote a diverse, inclusive, and equitable workplace, offering equal opportunities to all employees and applicants. We are committed to preventing discrimination and harassment of any kind, and we comply with all applicable laws related to non-discrimination in employment. We also provide reasonable accommodations for individuals with disabilities throughout the hiring process.