Data Scientist (AI)

TL;DR

Data Scientist (AI): Generating actionable insights to help product, data, and research teams prioritize efforts and identify opportunities in the AV 2.0 space with an accent on experimental and causal inference methods. Focus on pioneering data science methodologies in a complex and novel autonomous vehicle environment.

Location: Sunnyvale, California, USA

Company

hirify.global is a leading developer of Embodied AI technology, creating intelligent, mapless, and hardware-agnostic AI products for automakers to accelerate the transition from assisted to automated driving.

What you will do

• Build frameworks to synthesize complex video and simulation data to facilitate analytics-driven strategy.
• Formulate and iterate upon performance metrics to best measure success in an AV 2.0 world.
• Develop and deploy novel experimental techniques to improve signal-to-noise ratio and reduce time to feedback.
• Combine experiment methods with offline causal inference techniques.

Requirements

• 3+ years experience working in a Data Science role.
• Comfortable querying and building large datasets, writing production-level SQL for use in data-transformation pipelines.
• Prior experience designing robust real-world experiments (e.g. A/B) and critically evaluating test-statistics.
• Foundations in the fundamentals behind statistics: testing appropriate distributions, testing the assumptions behind frequentist stats.
• Proficient in using a statistical scripting language and data science/ML packages (e.g. python such as pandas, sklearn, statsmodels, scipy or R such as dplyr, caret, stats).
• Well-versed in summarising, visualising and communicating findings in an accessible and compelling way.
• Track record of influencing team direction through your findings.
• A bias towards deriving actionable insight that can be used to drive prioritisation and strategy for others.
• You are deeply curious about building something new and relish the idea of helping to define AV2.0 and how we build it.

Nice to have

• Practical experience with machine learning (e.g. pytorch). Passion to take research ideas to production.
• Track record of promoting statistical rigour and experimental best practices in your prior roles.
• Prior experience using causal inference/econometric techniques and bayesian methodologies for hypothesis testing.
• Prior experience using large datasets with distributed computing (e.g. spark, hadoop or other map-reduce tech).
• Experience working in a fast-moving tech company or startup.

Culture & Benefits

• Committed to creating a diverse, fair, and respectful culture that is inclusive of everyone.
• Value diversity, embrace new perspectives, and foster an inclusive work environment.
• Fast-paced environment where big problems ignite us and we embrace uncertainty.