Staff AI Scientist

About the Role

Key Responsibilities

• Practice leadership and communication skills to influence teams and to evangelize AI science across the organization.
• Collaborate with stakeholders to define success criteria and align model metrics with business goals.
• Work side-by-side with product managers, software engineers, and designers in designing experiments and minimum viable products.
• Lead technical work of a scrum team: initiating and designing model solutions, driving end-to-end architecture designs of the team's work, and holding the team accountable for high quality code, git, design, costs and implementation standards.
• Perform hands-on data analysis and modeling with large data sets, including discovering data sources, getting data access, cleaning up data, and making them “model-ready”.
• Apply data mining, NLP, and machine learning techniques to real-world problems and datasets.
• Run A/B tests to draw conclusions on the impact of your team's work and communicate results to peers and leaders.
• Communicate with partners to ensure successful delivery and integration of data science solutions.
• Proactively research, explore, and enable new ML technologies, keeping up with developments in academia and industry.
• Build and deploy machine learning models using analytical algorithms and deep learning approaches.

Requirements

• 4+ years of industry experience with AI science.
• BS, MS, or PhD in Statistics, Mathematics, Computer Science, Economics, Operations Research, or equivalent.
• Hands-on expertise in ML paradigms such as Causal-ML, supervised/unsupervised, Online, Bayesian, Reinforcement, or Deep Learning.
• Proficient in multiple optimization paradigms such as combinatorial optimization, gradient methods, or Bayesian optimization.
• Proficient in NLP techniques, Explainable AI, and ML frameworks.
• Experience with modern analytical tools and programming languages such as Python, Scala, Java, and/or R.
• Efficient in SQL, Hive, SparkSQL, etc.
• Comfortable working in a Linux environment.
• Experience with building end-to-end reusable pipelines from data acquisition to model output delivery.
• Strong oral and written communication skills, with the ability to explain complex concepts to non-technical users.

Nice to Have

• Experience in designing experiments and minimum viable products.
• Experience with large data sets and ETL processes.
• Knowledge of industry and academic developments in ML technologies.

Qualifications

• Bachelor's, Master's, or Doctoral degree in relevant fields.
• 4+ years of industry experience in AI or related fields.

Benefits & Perks

• Competitive compensation package with a strong pay-for-performance rewards approach.
• Eligible for a cash bonus, equity rewards, and benefits.
• Base pay range: $205,500 - $278,000, depending on experience and location.