Data Scientist Lead
Canoo's mission is to bring EVs to Everyone and build a world-class team to deploy this sustainable mobility revolution. We have developed breakthrough electric vehicles that are reinventing the automotive landscape with pioneering technologies, award-winning designs, and a unique business model that spans all owners in the full lifecycle of the vehicle. Canoo is starting production in 2022 and is distinguished by its pioneering and experienced team of technologists, engineers, and designers. With offices around the country, the company is scaling quickly and seeking candidates who love to challenge themselves, are motivated by purpose, and possess a strong desire to get things done. The Canoo Way Canoo's success is the direct result of our disciplined application of our core operating principles and drills, which are based on three main principles:
Think 80/20 (Important versus less important), Act 30/30 (Reduce waste and increase output), and Live 90/10 (We have each other's back). We hire based on MET - Mindset, Equipment and willingness to Train - and seek individuals that take accountability and deliver results while being Humble, Hungry to succeed, and Hunting for opportunities to win. We train our team to engage with each other by modulating between their intellect (iQ) and emotional intelligence (eQ), applying Facts, Finesse, and Force when they communicate. The principles and drills of the CANOO Way have been fundamental to our success, our ability to grow, continuously improve, innovate and are at the core of our day-to-day operations. Overview Work across all business domains to identify, get support for, plan, and build value add data products that leverage mobility data and methods and algorithms from data science, machine learning and artificial intelligence. Collaborate with agile team in the Data Office and across Canoo to advance the identification, collection, curation, and governance of data assets that have value for Canoo customers and Canoo. Collaborate with Data Engineers to build out and operationalize CI/CD pipeline for Data Science and AI/ML features and products. Responsibilities Ideate and collaborate with business leaders and product managers to drive innovation and thought leadership on AI/ML and model-based data products. Independently conduct hands-on research and development efforts (prototypes, proof of concepts and production/operational initiatives). Conceptualize, design, and develop advanced analytics & machine learning solutions that incorporate complex data into actionable insights and prescriptive models. Lead the development of best practices for formulating business challenges as a machine learning opportunity, sharing insights from feature exploration and model training/testing, operationalizing machine learning pipelines, and recommending business strategies that leverage the algorithms. Collaborate with data engineers, data visualization specialists, application developers and our clients to understand the clients' challenges and help craft solutions that solve their toughest, most critical problems. Qualifications Required Experience Demonstrable data science and/or machine learning experience that influenced/transformed enterprise-scale business processes (such as, Supply Chain, Customer Analytics, Marketing & Pricing, Risk & Fraud, Sentiment Analysis, Operations). Articulate how their analytics expertise applies across industry verticals (e.g. the candidate's prior experience may be financial services, but much of that experience can be translated to solve for similar/relevant challenges in healthcare or telecom). Excellence in a consultative setting, advising clients through the challenges of building complex analytic solutions that demand a multi-part engagement construct. 12
years of professional experience in advanced analytics/machine learning with progressive growth in mentoring and thought leadership responsibilities Graduate degree in a quantitative science or engineering with a proven track record of building data-intensive statistical, data mining and machine learning analytic models, with a focus on delivering business value and integration practicality Deep experience with one or more AI and ML frameworks like TensorFlow, PyTorch, Scikit-Learn and Keras. Advanced level knowledge of SQL. Advanced level experience with Python. Working knowledge of one or more cloud platform data and Analytics Services like AWS or GCP. Experience with one or more cloud data warehouse platforms like Snowflake or RedShift. Experience with streaming frameworks like Kafka. Experience working in a fast-paced agile team environment. Experience with containerization. Experience with CI/CD. Experience facilitating ideation and requirements workshops. Strong work ethic based on a strong desire to exceed expectations. Self-motivated with a curiosity and willingness to learn. Ability to build consensus with business partners and mediate when appropriate. Preferred Experience PhD in a quantitative discipline. Experience developing and operationalizing models on cloud platforms like AWS, Google, or Azure. Experience with Advanced Driver Assistance Systems (ADAS) features like Adaptive Cruise Control, Pre-Collision Assist and Park Assist. Experience working with OBD data and metrics. Experience working with IoT or fleet telematics data for safety, operational efficiency, and compliance. Experience with remote sensing systems like Radar, Lidar, Vision Cameras, GPS/GNSS systems with maps, Vehicle to Vehicle Communications. AI/ML Certifications on AWS, Google, or Azure. Physical Requirements for Non-Physical Positions While performing the duties of this job, employees may be required to sit for prolonged periods of time, occasionally bending or stooping, lifting up to 10 pounds, and prolonged periods of computer use. Reasonable Accommodations Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions of the position. What's Cool About Working Here Meaningful, challenging work that will redefine automotive landscape and make EVs available to everyone Comprehensive Health Insurance Equity Compensation Flexible Paid Time Off Casual workplace with an unbelievable feeling of energy
Salary Range:
$200K -- $250K
Minimum Qualification
Data Science & Machine LearningEstimated Salary: $20 to $28 per hour based on qualifications.
Think 80/20 (Important versus less important), Act 30/30 (Reduce waste and increase output), and Live 90/10 (We have each other's back). We hire based on MET - Mindset, Equipment and willingness to Train - and seek individuals that take accountability and deliver results while being Humble, Hungry to succeed, and Hunting for opportunities to win. We train our team to engage with each other by modulating between their intellect (iQ) and emotional intelligence (eQ), applying Facts, Finesse, and Force when they communicate. The principles and drills of the CANOO Way have been fundamental to our success, our ability to grow, continuously improve, innovate and are at the core of our day-to-day operations. Overview Work across all business domains to identify, get support for, plan, and build value add data products that leverage mobility data and methods and algorithms from data science, machine learning and artificial intelligence. Collaborate with agile team in the Data Office and across Canoo to advance the identification, collection, curation, and governance of data assets that have value for Canoo customers and Canoo. Collaborate with Data Engineers to build out and operationalize CI/CD pipeline for Data Science and AI/ML features and products. Responsibilities Ideate and collaborate with business leaders and product managers to drive innovation and thought leadership on AI/ML and model-based data products. Independently conduct hands-on research and development efforts (prototypes, proof of concepts and production/operational initiatives). Conceptualize, design, and develop advanced analytics & machine learning solutions that incorporate complex data into actionable insights and prescriptive models. Lead the development of best practices for formulating business challenges as a machine learning opportunity, sharing insights from feature exploration and model training/testing, operationalizing machine learning pipelines, and recommending business strategies that leverage the algorithms. Collaborate with data engineers, data visualization specialists, application developers and our clients to understand the clients' challenges and help craft solutions that solve their toughest, most critical problems. Qualifications Required Experience Demonstrable data science and/or machine learning experience that influenced/transformed enterprise-scale business processes (such as, Supply Chain, Customer Analytics, Marketing & Pricing, Risk & Fraud, Sentiment Analysis, Operations). Articulate how their analytics expertise applies across industry verticals (e.g. the candidate's prior experience may be financial services, but much of that experience can be translated to solve for similar/relevant challenges in healthcare or telecom). Excellence in a consultative setting, advising clients through the challenges of building complex analytic solutions that demand a multi-part engagement construct. 12
years of professional experience in advanced analytics/machine learning with progressive growth in mentoring and thought leadership responsibilities Graduate degree in a quantitative science or engineering with a proven track record of building data-intensive statistical, data mining and machine learning analytic models, with a focus on delivering business value and integration practicality Deep experience with one or more AI and ML frameworks like TensorFlow, PyTorch, Scikit-Learn and Keras. Advanced level knowledge of SQL. Advanced level experience with Python. Working knowledge of one or more cloud platform data and Analytics Services like AWS or GCP. Experience with one or more cloud data warehouse platforms like Snowflake or RedShift. Experience with streaming frameworks like Kafka. Experience working in a fast-paced agile team environment. Experience with containerization. Experience with CI/CD. Experience facilitating ideation and requirements workshops. Strong work ethic based on a strong desire to exceed expectations. Self-motivated with a curiosity and willingness to learn. Ability to build consensus with business partners and mediate when appropriate. Preferred Experience PhD in a quantitative discipline. Experience developing and operationalizing models on cloud platforms like AWS, Google, or Azure. Experience with Advanced Driver Assistance Systems (ADAS) features like Adaptive Cruise Control, Pre-Collision Assist and Park Assist. Experience working with OBD data and metrics. Experience working with IoT or fleet telematics data for safety, operational efficiency, and compliance. Experience with remote sensing systems like Radar, Lidar, Vision Cameras, GPS/GNSS systems with maps, Vehicle to Vehicle Communications. AI/ML Certifications on AWS, Google, or Azure. Physical Requirements for Non-Physical Positions While performing the duties of this job, employees may be required to sit for prolonged periods of time, occasionally bending or stooping, lifting up to 10 pounds, and prolonged periods of computer use. Reasonable Accommodations Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions of the position. What's Cool About Working Here Meaningful, challenging work that will redefine automotive landscape and make EVs available to everyone Comprehensive Health Insurance Equity Compensation Flexible Paid Time Off Casual workplace with an unbelievable feeling of energy
Salary Range:
$200K -- $250K
Minimum Qualification
Data Science & Machine LearningEstimated Salary: $20 to $28 per hour based on qualifications.
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