Job summary
Job post source
This job is directly from Aura
Job overview
The Principal Data Scientist at Aura leads the development and optimization of advanced ML and LLM models to enhance digital safety products, playing a crucial role in shaping the company's AI strategy and delivering impactful, privacy-preserving solutions.
Responsibilities and impact
The role involves developing scientifically sound AI tools for digital safety, leading cross-functional teams, translating complex data into actionable insights, building reproducible research pipelines, collaborating on clinical and product data analyses, and providing biostatistical expertise for scientific publications.
Compensation and benefits
The position offers a competitive salary range of $180,000 to $230,000, along with generous health and wellness benefits, retirement plans, parental leave, and a supportive work-life package.
Experience and skills
Candidates should have a Master's degree (PhD preferred), 8+ years of data science experience including generative AI and prompt engineering, expertise in biostatistics, experience with clinical or youth healthcare product teams, and skills in building transparent research pipelines; familiarity with large datasets, scientific publishing, and tools like Databricks, python/pySpark, MLflow, R, or SAS is a plus.
Career development
Aura offers professional growth through involvement in cutting-edge AI projects, collaboration with clinical and product experts, and opportunities to contribute to peer-reviewed scientific research.
Work environment and culture
Aura values inclusivity, equal employment opportunity, and accessibility, fostering a welcoming environment that supports employee well-being and diversity.
Company information
Aura is a digital safety company with over 400 employees worldwide, focused on protecting customers from digital threats through intelligent safety products, guided by experienced leadership with a history of scaling startups.
Team overview
The candidate will work closely with cross-functional teams including data scientists, data engineers, product managers, and clinical experts to deliver AI-driven digital safety solutions.
Unique job features
The role uniquely combines advanced AI development with clinical and mental health research, emphasizing scientific integrity, privacy, and real-world impact in digital safety and well-being.
Company overview
Aura is a technology company specializing in digital security and privacy solutions. They provide a comprehensive suite of services including identity theft protection, credit monitoring, and VPN services to safeguard personal information and enhance online privacy. Aura generates revenue through subscription-based models, offering individual and family plans that cater to various security needs. Founded in 2019, Aura has quickly established itself as a leader in the cybersecurity industry, driven by its mission to make the internet safer for everyone. The company's innovative approach and commitment to user-friendly solutions have contributed to its rapid growth and positive reputation in the market.
How to land this job
Position your resume to highlight your expertise in developing and validating advanced ML and LLM models, especially those related to digital safety and mental health, aligning with Aura's mission to create a safer internet.
Emphasize your experience leading cross-functional teams including data scientists, engineers, and product managers, and your ability to bridge complex business challenges with cutting-edge AI solutions.
Apply through multiple channels such as Aura's corporate careers page and LinkedIn to maximize your visibility and increase your chances of landing an interview.
Connect with current data science and AI team members at Aura on LinkedIn; a good ice breaker could be commenting on recent AI initiatives or publications Aura has released, or expressing your enthusiasm for their mission in digital safety and mental health.
Optimize your resume for ATS by incorporating keywords from the job description like 'machine learning,' 'LLM models,' 'biostatistics,' 'data pipelines,' 'privacy-preserving AI,' and 'clinical data analysis' to ensure it passes initial automated screenings.
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