Senior Applied Scientist

Responsibilities

• Lead end-to-end development of machine learning models from problem formulation and experimentation through deployment and performance evaluation.
• Design and evaluate advanced modeling approaches to improve predictive accuracy, robustness, and operational effectiveness.
• Improve existing models through feature development, experimentation, and rigorous statistical analysis.
• Partner with engineering, product, and business stakeholders to translate requirements into measurable machine learning objectives.
• Guide technical decisions, review scientific methodologies, and share expertise across the team.

Requirements

• Bachelor’s degree in computer science, engineering, mathematics, statistics, or a related field, or equivalent practical experience.
• At least 3 years of experience developing and evaluating machine learning models or applying statistical methods to production-oriented problems.
• Experience developing machine learning solutions with Python and established machine learning frameworks.
• Experience designing and evaluating experiments using statistical methods and quantitative performance metrics.
• Experience implementing, deploying, or maintaining machine learning models in production environments.
• Preferred qualifications include an advanced degree in a quantitative field, knowledge of ensemble learning, deep learning, or probabilistic modeling, and experience with large-scale data processing or distributed machine learning systems.
• Ability to evaluate tradeoffs among model performance, interpretability, reliability, and computational efficiency, and communicate scientific findings to technical and business teams.

Benefits

• Remote position available in the U.S. and Canada outside Quebec, with most teams meeting onsite once or twice per quarter for 2–4 consecutive days.
• Benefits include medical, dental, vision, wellness resources, retirement plans with company matching, paid time off, sick leave, company holidays, and paid family and parental leave.
• Additional benefits include equity grants, an employee stock purchase plan for eligible U.S. employees, health savings account contributions, life and disability insurance, fertility and caregiving support, and an employee assistance program.
• Employees receive annual wellness and productivity allowances, financial wellness resources, team events, and employee resource groups.
• Office perks include catered lunches and stocked micro-kitchens in the Bay Area, Austin, Columbus, and New York City.